TitleAnalysis of Transcriptional Responses in Plants Related withInduced Systemic Resistance by Plant Growth Promoting Fungi(本文(Fulltext) )

Author(s) Most. Hushna Ara Naznin

Report No.(DoctoralDegree) 博士(農学) 甲第629号

Issue Date 2014-03-13

Type 博士論文

Version ETD

URL http://hdl.handle.net/20.500.12099/49109

※この資料の著作権は、各資料の著者・学協会・出版社等に帰属します。

1

Analysis of Transcriptional Responses in Plants Related with Induced Systemic Resistance by Plant Growth Promoting Fungi

( )

2013

The United Graduate School of Agricultural Sciences,

Gifu University

Science of Biological Resources

(Gifu University)

Most. Hushna Ara Naznin

2

Analysis of Transcriptional Responses in Plants Related with Induced Systemic Resistance by Plant Growth Promoting Fungi

( )

Most. Hushna Ara Naznin

3

TABLE OF CONTENTS

Page

CHAPTER 1

GENERAL INTRODUCTION 5

CHAPTER 2

Analysis of volatile organic compounds emitted by plant growth promoting 12

fungus Phoma sp. GS8-3 for growth promotion effects in tobacco

CHAPTER 3

Systemic resistance induced by volatile organic compounds emitted by 38

plant growth-promoting fungi in Arabidopsis thaliana

CHAPTER 4

Analysis of microarray data and prediction of transcriptional regulatory 67

elements related with Disease resistance

CHAPTER 5

Construction of luciferase based vectors using synthetic promoters and their 89

functional analysis in planta

SUMMERY AND CONCLUSION 112

ACKNOWLEDGMENT 115

LITERATURE CITED 117

4

CHAPTER 1

GENERAL INTRODUCTION

GENERAL INTRODUCTION

5

Food production is affected by a myriad of factors including, but not limited to, decreasing area

of arable land, pestilence, climate change, underdeveloped infrastructures, and political factors.

Research continues to increase agricultural yields and improve practices, particularly in

developing countries. The reliance on fertilizers and pesticides, which are inappropriately

managed, has significantly compromised human health and the integrity of natural resources that

support life itself, such as soil and water. This has led to the development of the concepts of

sustainability. Sustainability can be defined as the “successful management of resources to

satisfy changing human needs while maintaining or enhancing the quality of the environment

and conserving resources” (13). Specially, sustainability in agriculture can be characterized by,

for example, the maintenance of soil fertility and structure over a long period of time such that

the economic yields from crops can be achieved through minimum inputs. However, it is not

easy to develop any form of agriculture that could be truly sustainable. As an alternative, the

modification of strategies or practices is required such that chemical fertilizer and pesticide

inputs are reduced but not eliminated, and that there is maximum use of the soil microbiota like

the beneficial microorganisms which have innate roles in nutrient capture and cycling nutrients

to the plant root system.

Currently, beneficial micro-organisms are increasingly used as inoculants for biofertilization,

phytostimulation and biocontrol, because reduced use of fertilizers and fungicides in agricultural

production is necessary to help maintain the ecosystems and to develop sustainable agriculture.

The use of both bio-fertilizers and biocontrol systems can have minimal affect on environment

and such strategies have been widely researched. Plant growth-promoting rhizobacteria (PGPR)

and plant growth-promoting fungi (PGPF) are naturally occurring soil microorganisms that

colonize roots and stimulate plant growth. Such bacteria and fungi have been applied to a wide

6

range of agricultural species for the purpose of growth enhancement, including increase seed

emergence, plant weight, crop yields and disease control (47, 60). The mechanisms of plant

growth promotion by PGPR and PGPF have been reported, including plant hormones production

(70, 72, 118) substrate degradation (mineralization) and suppression of deleterious

microorganisms (48, 73).

Plant growth is influenced by an abundance of abiotic and biotic factors. Plant growth hormones

dominatingly affect plant growth, whereas the photosynthetic rate is dominated by temperature,

irradiance and gaseous atmosphere (42). These physiological functions have been utilized as

classical plant growth regulators. However, along with the composition of the nutrient medium,

the composition of the gaseous atmosphere is another important factor for proper growth and

development of plants (12). Several gaseous components are present in the atmosphere especially

nitrogen, oxygen, carbon dioxide and different types of volatile compounds produced by

surrounding organisms including the plant itself (16, 103). Changes in these components during

different physiological functions in vitro largely affect the photosynthesis and other biological

functions of the plant (16).

Recently, it has been demonstrated that plants have evolved the capacity to release and detect

volatile organic compounds (VOCs) in their environment, and plant growth is promoted by

VOCs from beneficial microorganisms (95, 124). VOCs, the major source of secondary

metabolites and important components in ecosystems (10), are intensively studied due to their

access as a biocontrol resource. VOCs characterized by low molecular weight and high vapor

pressure are produced by all organisms as part of their normal metabolism, and play important

roles in communication within and between organisms (98). VOCs mediated interactions among

plant-plant, plant-insect and bacteria–plant have been frequently documented (24, 26, 52, 95, 99).

7

Plants also perceive the presence of pathogenic microbes via metabolites derived from the

pathogen and activate defensive responses against the pathogens (2). Though the details of the

molecular interactions are unknown as of now, low-molecular-weight plant volatiles such as

terpenes, jasmonates and green leaf components have been identified as potential signal

molecules for the plant (33). Koitabashi (63, 64) reported that a filamentous fungus isolated from

the wheat leaf produces volatile materials that could suppress diseases and promote growth of

different plants. Subsequently, volatile- producing fungus Muscodor albus was reported to have

the capacity of growth enhancement and biological control of soil-borne diseases (80). Although

the signaling network between plants and microbes has been extensively studied for the past 20

years, little is known on the role of microbial VOCs in regulating plant growth and development.

Many reports have focused on the effects of volatiles produced by rhizobacteria or plant growth

promoting rhizobacteria on plant disease control. Several volatiles produced by rhizobacteria

have exhibited antibacterial or antifungal activities (51). Two volatiles, 2,3-butanediol and

acetoin (3-hydroxy-2 butanone), produced by Bacillus subtilis and Bacillus amyloliquefaciens

have been identified as important factors in inducing systemic resistance and promoting plant

growth (96, 32). Volatiles produced by a few strains of Streptomyces are also reported to have

potential for biocontrol (122, 69).

While most studies have focused on the interaction between rhizobacteria and plant pathogens,

little is known about the plant response to VOC emitted by PGPF and the resistance that is

conferred.

8

Therefore, in the present study, we aimed to establish whether the PGPF-released VOC can

induce systemic resistance in plants, and if they can, to determine what types of signaling

pathways are involved in this ISR.

Plants respond to adverse environmental stress and pathogen attack by expressing specific genes

and synthesizing a large number of stress proteins that have putative roles in stress adaptation

and plant defense (110, 92). The signals that mediate systemic responses must be transmitted

rapidly throughout the plant and may involve cell-to-cell signaling. Putative systemic signals

include ethylene (29), salicylic acid (27), jasmonic acid (35), and abscisic acid (133).

Communication between these plant hormones might modulate the expression of abiotic and

biotic stress–responsive genes in plants. However, the interactions between these hormone-

mediated signal pathways and molecular mechanisms governing their cross-regulation have

remained generally unresolved.

An example of a PGPF is Penicillium simplicissimum GP17-2, which was found to control soil-

borne diseases effectively (47). Examination of local and systemic gene expression revealed that

culture filtrate of GP17-2 modulate the expression of genes involved in both the SA and JA/ET

signaling pathways. Phytohormones are acting on this signal transduction alone or interact each

other in a cooperative, competitive or interdependent way. This relationship between

phytohormones is a part of the transcriptional network for complex phytohormones responses.

These transcriptional networks are biologically important for plants to respond against any kind

of environmental stress. Promoter regions of stress-inducible genes contain cis-acting elements

involved in stress-responsive gene expression. Precise analysis of cis-acting elements and their

transcription factors can give us an accurate understanding of regulatory systems in stress-

responsive gene expression. The DNA microarray has recently emerged as a powerful tool in

9

molecular biology research, offering high throughput analysis of gene expression on a genomic

scale. Microarrays have already been used to characterize genes involved in the regulation of

circadian rhythms, plant defense mechanisms, oxidative stress responses, and phytohormone

signaling. Microarray data can serve a long list of up-regulated as well as genes with no response

to stresses, and thus has a potential to identify corresponding cis-regulatory elements. In

Arabidopsis plant, thousands of genes have been found as up-regulated and down-regulated from

microarray analysis of the stress-inducible genes (Kubota et al. unpublished). In order to identify

cis-regulatory elements without using microarray there are some other methods have also been

established. A large number of Arabidopsis cis-regulatory elements have been identified by a

recently developed bioinformatics methodology named LDSS (Local Distribution of Short

Sequences) (127). There are 308 octamers have successfully been detected that belong to a group

of putative cis-regulatory elements, Regulatory Element Group (REG), in addition to novel core

promoter elements (131) by applying LDSS method in Arabidopsis genome. Biological role of

most of the REG is still not very clear. In order to give biological annotation to cis-regulatory

elements, one of the best methods is to analyze the microarray data and to predict cis-elements

from the genes response to environmental stress.

In my laboratory, microarray analysis to see transcriptional response of Arabidopsis treated with

GP17-2 in roots has been performed. Taking advantage of the in house data, I analyzed the

microarray data in detail, by comparing selected public microarray data of pathogen,

phytohormones, hydrogen peroxide (H2O2), and wound responses. Utilizing the microarray data,

I achieved in silico promoter analysis in order to reveal participating cis-regulatory elements

involved in the GP17-2-mediated ISR. An octamer-based frequency comparison method that has

been developed in our laboratory was used for the prediction.

10

Some promoters are known to be activated by osmotic stress, high salt, drought, or ABA

treatment (125, 123). Moreover, different cis-acting elements in these promoters are involved in

stress-responsive gene expression (126). ABRE (ABA-responsive element) and DRE/CRT

(dehydration-responsive element/C repeat) are major cis-acting elements in abiotic stress-

inducible gene expression. DRE/CRT elements with the core sequence C/DRE (GCCGAC) play

an important role in regulating gene expression in ABA-independent regulatory systems and can

be found in promoter regions of many dehydration-, high-salt-, and cold-stress inducible genes in

Arabidopsis, such as rd29A, kin1, and cor15a (6,123, 54). Various types of ABRE-like

sequences have been reported, including the G-box sequence (CACGTG), which is present in a

large number of environmentally regulated genes (79). Other cis-regulatory elements, such as

MYB (C/TAACNA/G), MYC (CANNTG), LTRE (CCGAC) play key roles in activating gene

expression in response to osmotic stress and/or ABA (6, 1, 87).

Applications in plant genetic engineering with transcription factors driven by stress-induced

promoters provide an opportunity to improve the stress tolerance of crops (121). However, the

activities of native promoters identified so far have certain limitations, such as low expression

activity and low specificity. A series of synthetic promoters for higher-level expression of

foreign genes has been reported in the literature (82, 94, 102, 61,11). With the information

currently available on the regulatory mechanisms of abiotic stress tolerance in plants, it is now

feasible to construct strong inducible promoters artificially. Thus, in the current study, I have

selected cis-regualtory elements derived from stress-induced promoters (e.g. PGPF,

phytohormone) in Arabidopsis, to construct artificial promoters. The pattern of inducibility

driven by these artificial synthetic promoters was characterized in stable transgenic Arabidopsis

by monitoring expression of the luciferase (LUC) reporter gene, upon exposure of these plants to

11

various stress conditions. In addition, promoter activity was assessed through luminescence

estimation of LUC expression in transgenic plants under various stress conditions (biotic and

phytohormone) as compared to the wild type Col-0 and /or vector control.

Therefore, this study was conducted to explore the molecular characterization and transcriptional

responses during ISR by plant growth promoting fungi (PGPF). To achieve the goal, at first the

volatile organic compounds were isolated from PGPF and analyzed for growth promotion and

disease suppression effect in the first two chapters. Then microarray data of PGPF treated gene

expression were analyzed and compared with phytohormone responses to find out the

involvement of phytohormones during ISR induced by PGPF. Analyzing the microarray data

with the help of bioinformatics, I have extracted some putative cis-regulatory elements, prepared

synthetic vectors by inserting them in luciferase reporter gene based vector. Finally, the synthetic

vectors were subjected to in vivo analysis to examine the biological response against different

biotic and abiotic stress.

12

CHAPTER 2

Analysis of volatile organic compounds emitted by plant growth- promoting fungus Phoma sp. GS8-3 for growth

promotion effects in tobacco

13

Analysis of volatile organic compounds emitted by plant growth-promoting fungus Phoma sp. GS8-3 for growth promotion effects in

tobacco

2.1 INTRODUCTION

Plant growth is influenced by an abundance of abiotic and biotic factors. Plant growth hormones

dominatingly affect plant growth, whereas the photosynthetic rate is dominated by temperature,

irradiance and gaseous atmosphere (42). These physiological functions have been utilized as

classical plant growth regulators. However, along with the composition of the nutrient medium,

the composition of the gaseous atmosphere is another important factor for proper growth and

development of plants (12). Several gaseous components are present in the atmosphere especially

nitrogen, oxygen, carbon dioxide and different types of volatile compounds produced by

surrounding organisms including the plant itself (16, 103). Changes in these components during

different physiological functions in vitro largely affect the photosynthesis and other biological

functions of the plant (16).

Recently, it has been demonstrated that plants have evolved the capacity to release and detect

volatile organic compounds (VOCs) in their environment, and plant growth is promoted by

VOCs from beneficial microorganisms (95,124). VOCs, the major source of secondary

metabolites and important components in ecosystems (10), are intensively studied due to their

access as a biocontrol resource. VOCs characterized by low molecular weight and high vapor

pressure are produced by all organisms as part of their normal metabolism, and play important

roles in communication within and between organisms (98). VOCs mediated interactions among

plant-plant, plant-insect and bacteria–plant have been frequently documented (24, 26, 52, 95, 99).

14

Plants also perceive the presence of pathogenic microbes via metabolites derived from the

pathogen and activate defensive responses against the pathogens (2). Though the details of the

molecular interactions are unknown as of now, low-molecular-weight plant volatiles such as

terpenes, jasmonates and green leaf components have been identified as potential signal

molecules for the plant (33, 34). Koitabashi (63,64) reported that a filamentous fungus isolated

from the wheat leaf produces volatile materials that could suppress diseases and promote growth

of different plants. Subsequently, volatile- producing fungus Muscodor albus was reported to

have the capacity of growth enhancement and biological control of soil-borne diseases (80).

Although the signaling network between plants and microbes has been extensively studied for

the past 20 years, little is known on the role of microbial VOCs in regulating plant growth and

development.

Currently, beneficial micro-organisms are increasingly used as inoculants for biofertilization,

phytostimulation and biocontrol, because reduced use of fertilizers and fungicides in agricultural

production is necessary to help maintain the ecosystems and to develop sustainable agriculture.

The use of both bio-fertilizers and biocontrol systems can have minimal affect on environment

and such strategies have been widely researched. Plant growth-promoting rhizobacteria (PGPR)

and plant growth-promoting fungi (PGPF) are naturally occurring soil microorganisms that

colonize roots and stimulate plant growth. Such bacteria and fungi have been applied to a wide

range of agricultural species for the purpose of growth enhancement, including increase seed

emergence, plant weight, crop yields and disease control (47, 60) The mechanisms of plant

growth promotion by PGPR and PGPF have been reported, including plant hormones production

(70, 72, 118), substrate degradation (mineralization) and suppression of deleterious

microorganisms (48, 73).

15

In the past few years the role of volatile emissions from rhizobacteria in plant development has

been widely studied. Ryu et al. (95) first reported a blend of airborne chemicals released from

specific strains of PGPR, Bacillius subtillis GB03 and Bacillius amyloliquefaciens IN937a,

which promoted growth of Arabidopsis thaliana seedlings. Gutiérrez-Luna et al. (41) also

reported that VOCs from some strains of Bacillius sp. has growth promotion effect . While most

studies have focused on the effect of VOCs released from PGPR and plant pathogens, little is

known about the molecular mechanisms of response and resistance offered by PGPF- released

VOCs.

Previously, different PGPF isolates like Phoma sp. (GS8-3, GS8-1) and Penicillium

simplicissimum (GP17-2) have been reported for their growth promotion effect (77,78,107,108,

115). However, VOCs from these have not been analyzed. The first report regarding the growth

promotion effect of VOCs produced by PGPF was by Yamagiwa et al. (124) where they

introduced a new PGPF, Talaromyces wortmannii having growth promotion effect on several

plant species such as Brassica campestris, Arabidopsis thaliana, Phaseolus vulgaries, Nicotiana

benthamiana and Cucumis sativas. The major volatile component isolated from that PGPF was a

terpenoid-like volatile β-caryophyllene which significantly promoted plant growth and induce

resistance of turnip (124).

Considering that the fungi produce a wide range of VOCs (32) and VOCs produced from

microorganisms play important role in plant growth, we aimed to analyze plant growth

promotion effect of VOCs released from previously reported plant growth promoting fungus

Phoma sp. GS8-3.

16

2.2 MATERIALS AND METHODS

2.2.1 Fungal cultures

One hundred fungal isolates were used in this experiment. All of the isolates were obtained from

the plant pathology laboratory of Gifu University. Air borne fungi were isolated from leaves of

turf grass around Gifu city and the soil borne fungi were isolated from the rhizosphere of

cucumber, tomato and leaf mustard. Most of the isolates were identified by sequence

comparison in the ITS regions of the rRNA gene including 5 of the selected fungi: Cladosporium

sp. (D-c-4), Ampelomyces sp. (D-b-7, F-a-3), Mortierella sp. (U-c-1) and Phoma sp. (GS8-3)

(data not shown). The fungal isolates were cultured on potato dextrose agar (PDA), and the

periphery of actively growing cultures were cut with a cork borer of 5 mm diameter and used in

the experiment. The fungal cultures were maintained on PDA slants and stored at 50 C.

2.2.2 Preparation of Plant materials

Seeds of Nicotiana tabacum L. cv. Xanthi-nc were surface-sterilized (70% ethanol soaking for 2

minutes, followed by 5% sodium hypochlorite soaking for 2 minutes), rinsed (five times) in

sterile distilled water, and placed on petri dishes containing Murashige and Skoog salt (MS)

medium (Wako) containing 0.8% agar and PH was adjusted to 5.7. The seeds were incubated in

growth cabinets (Nihon ika kikai seisakusho, LH-100S) set to a 12-h-light/12-h-dark cycle at 25

oC .

2.2.3 Screening of fungal isolates showing plant growth promotion

Plastic petri dishes (90×15 mm) containing a center partition (I plates; Atekuto) were prepared

with 5 ml MS solid medium on one side, and 5 ml PDA on the other side. Fourteen days old

17

tobacco seedlings (10 seedlings per plate) were transferred to the MS solid medium side of the I

plates. Treatments were done by inoculating the I plates with a disk of fungal isolate on the

center of PDA medium. Control was maintained by using PDA medium without fungal disk. The

plates were sealed with parafilm and arranged in a randomized design within the growth cabinets

and incubated at 25 oC with a 12-h-light/12-h-dark photoperiod.

2.2.4 Design of screening of fungal isolates

Test fungal isolates were selected randomly considering the origin of isolates and pattern of

growth promotion. Among the 7 test fungi, 4 were selected from the air-borne fungal group:

Cladosporium sp. (D-c-4), Ampelomyces sp (D-b-7and F-a-3) and C-b-9 (unidentified); whereas

the other 3: Phoma sp. (GS8-3), E-a-2 (unidentified) and Mortierella sp. (U-c-1) were from the

soil borne fungal group. Considering the pattern of growth promotion effects, D-c-4

(Cladosporium sp.), GS8-3 (Phoma sp.), and D-b-7 (Ampelomyces sp.) were selected from the

group of fungi that have higher growth promotion effect; whereas F-a-3 (Ampelomyces sp.) was

selected from the medium group and unidentified E-a-2 and C-b-9 and U-c-1 (Mortierella sp.)

were selected from the fungi having lower growth promotion effect.

2.2.5 Measurement of CO2 regulation by the test fungus

The test fungal isolates were inoculated in a 300 ml Erlenmeyer flask containing 100 ml PDA

and cultured in an incubator set to 12-h-light / 12-h-dark cycle for 7 days at 250 C. Three, 5, 7, 9,

12 and 14 days after inoculations, CO2 concentration in the jar was measured by a CO2 detector.

2.2.6 Analysis of volatiles produced from a selected fungal isolates GS8-3 for plant growth

promotion effect

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The assay was performed in two Erlenmeyer flasks that were tied in a glass tube with adapters

for air inlet and outlet. The first Erlenmeyer flask was prepared with 100 ml PDA medium and

the second flask was prepared with 100 ml MS solid medium. The tobacco seedlings incubated

for 14 days (20 seedlings per a flask) were transferred to the MS solid medium containing flask.

PGPF isolate GS8-3 was used as test fungus and incubated on the PDA medium of the

Erlenmeyer flask. Air was passed over the fungal culture to the plant culture one-way at 10

ml/min. In another set, a charcoal and silica-gel tube (SIBATA) was used as an absorbent of

the volatile compounds produced by the test fungus to compare the effect of the compounds on

plant growth. The absorbent was connected at the middle part of the glass tube which was tied to

the fungal culture flask connected to the plant culture. Control was maintained by using PDA

medium without fungal disk. The whole set up was incubated were incubated at 250 C with a 12

h-light/12 h-dark photoperiod for 14 days. The tube was moved every third day and new one was

set.

2.2.7 Measurement of atmospheric CO2 in vitro and analysis of its effect on plant growth

Three sets of I plates were used in this experiment. The I plates were prepared with 5 ml MS

solid medium on one side, and 5 ml PDA on the other side. In the first design, 14 days old

tobacco seedlings were transferred to the MS solid medium side (10 seedlings per plate) and the

PDA side of the I plates were inoculated with a disk containing GS8-3. In the second design, the

PDA side of I plates contained only PDA without fungus. And in the third design, the PDA side

of the I plates were inoculated with a disk containing GS8-3 but the MS solid medium were

without plants. Then the I plates were placed in the AnaeroPack rectangular jar (2.5 liters)

(Mitsubishi Gas Chemical, Tokyo, Japan) that contained an AnaeroPack MicroAero (Mitsubishi

Gas Chemical, Tokyo, Japan). The AnaeroPack MicroAero is a non disposable oxygen-

19

absorbing and carbon dioxide-generating agent for use in anaerobic jar. The experiment was

performed under 7 % (vol) preliminary CO2 concentration with an AnaeroPack MicroAero in the

jar. The jar was placed in growth cabinets set to a 12-h-light / 12-h-dark cycle for 7 days at 25

oC. Tobacco plants with and without fungus were also grown for comparing plant growth in the

jar without Anaeropack MicroAero. The CO2 concentration and plant growth was compared

between the treatments with or without the Anaeropack MicroAero. There were five replicates

for each treatment and the CO2 concentration in the jar was measured by CO2 detector (New

Cosmos Electric Co., Osaka, Japan) at 1, 3, 5 and 7 days after treatment.

2.2.8 Extraction and Analysis volatile metabolites

GS8-3 was cultured in 10 ml solid phase micro extraction (SPME) vials (Supelco, Sigma-Aldrich

Co. US) for 3, 5, 7 and 9 days. The volatile metabolites were extracted by headspace SPME

during 30 min at 25 oC. Polydimethylsiloxane / Divinylbenzene (PDMS/DVB) (65μm) fibers

were used for volatiles profiling. Fibers were obtained from Supelco, and conditioned prior to

analyses according to the manufacturer’s recommendations.

GC-MS: A Hewlett-Packard 5890 gas chromatograph equipped with a split injector HP-5 MS

capillary column (30 m length, 0.25 mm i.d.) was combined by direct coupling to a Hewlett-

Packard 5972 A mass spectrometer. Working conditions were: injector 250 oC, transfer line to

MS system 250 oC, oven temperature-start 40 oC, hold 2 min, programmed from 40 to 200 oC at

10 oC min-1, from 200 to 250 oC at 15 oC min-1, hold 5 min; carrier gas (He) 1.0 ml min-1;

injection of the analytes was done in split mode (1/10); electron impact ionization 70 eV. Peak

areas (of total ion current) were used for comparison of volatile compound fractions. Compounds

were identified using the US National Institute of Standards and Technology (NIST) Mass

20

spectral Library or by comparison of retention times and spectra with those of authentic

standards and Kovats retention indices with literature data.

2.2.9 Analysis of plant growth promoting effect of volatile organic compounds produced by

PGPF isolate GS8-3

I plates were prepared with 5 ml MS solid medium on one side. Fourteen-day old pre-germinated

tobacco seedlings were transferred to the side of I plates. The compounds identified through GS-

MS analysis were purchased (synthetic chemicals) to carry out plant growth promotion test. The

compounds were diluted in CH2Cl2, or the solvent alone was mixed with 0.1 lanolin, and 20 μl of

the resulting suspension was applied to a sterile paper disk (d=1cm). Each of the compounds was

tested for plant growth promoting effect by placing 1.8×10-4 and 1.8×10-2 μg singly and in

combination with the compounds, on sterile filter paper discs placed on the blank side of I

plates. The plates were sealed with parafilm and arranged in a randomized design within the

growth cabinets and incubated at 25 oC with a 12-h-light/12-h-dark photoperiod. There were four

replications for each treatment and the experiments were repeated three times.

2.2.10 Statistical Analysis

Data of growth promotion was analyzed by the analysis of variance (ANOVA). The significance

of effect of fungal treatments was determined by the magnitude of the F value (P = 0.05). When

a significant F test was obtained for treatments, separation of means was accomplished by

Fisher’s protected least significant difference (LSD) test.

21

2.3 RESULTS

2.3.1 Screening of fungal isolates showing plant growth promotion

One hundred fungal isolates were screened for the growth promotion effect in tobacco plant.

Almost all of the fungal isolates were found to promote plant growth except the isolate U-c-1.

Among them, 70 isolates were found to promote plant growth almost double compared to control

treatment after 7 days of transplanting (Fig. 2.1). Seven isolates such as D-c-4 (Cladosporium

sp.), D-b-7 (Ampelomyces sp.), F-a-3 (Ampelomyces sp.), GS8-3 (Phoma sp.), C-b-9

(unidentified air borne fungus), U-c-1 (Mortierella sp.) and E-a-2 (unidentified soil borne

fungus) were randomly selected for rescreening for their growth promotion effect in tobacco

maintaining time course as 3, 5, 7, 10 and 14 days after treatment. All isolates showed

significantly higher growth at 14 days comparing to control triggering gradual growth promotion

until 7 days and then with a sharp increase of plant fresh weight (Fig. 2.2). U-c-1 was found to

have comparatively poor growth promotion effect while D-c-4 has the highest that validated the

preliminary result in which this isolate belonged to the top group isolates. In this experiment, I

plates (Atekuto) were used which have a central partition that avoids physical contact between

the fungus and the plant seedlings and allowing only airborne signal transmission.

2.3.2 Measurement of CO2 production by the test fungus and analysis of its effect on plant

growth

Since CO2 plays an important role in plant growth it is necessary to measure CO2 regulation by

the test fungal isolates and their role on plant growth. Test isolates showed variable trend in CO2

production. D-b-7 and D-c-4 showed highest production of CO2 at 14 days after inoculation that

indicates a positive correlation between the increase of CO2 regulation and growth promotion of

22

tobacco though both the patterns are different (Fig. 2.3 and Fig. 2.2). However, F-a-3 showed

higher rate of CO2 production for the first 9 days but subsequently it gradually decreased. In the

case of GS8-3, CO2 concentration showed an increase for the first 7 days but after that

marginally decreased. In the case of U-c-1 and E-a-2, slowly increasing CO2 concentration

pattern was noticed whereas C-b-9 was notable in showing an exceptionally slow increase in CO2

production. These results suggest that F-a-3, C-b-9 and GS8-3 could promote growth of tobacco

at 14 days after inoculation despite of the decrease in CO2 production. Among the seven fungi,

GS8-3 was selected for further analysis. Because Phoma sp. GS8-3 has previously been

reported as a PGPF, as well as a biocontrol agent (Meera et al. 1995; Meera et al. 1994; Shivanna et

al. 1995; Shivanna et al. 2005; Sultana et al. 2009).

2.3.3 Analysis of volatile substances produced from selected fungal isolate for plant growth

promotion effect

To confirm the growth promotion effect of the volatile chemicals released from the test fungal

isolate GS8-3, another experiment was done by using absorbent of volatile substances. GS8-3

inoculated seedlings in which absorbent was not used showed more than 7 times growth

promotion whereas fungus inoculated plants where absorbent was used showed 1.5 times growth

promotion over control (Fig. 2.4). This result confirms the positive effect of airborne chemical

signaling produced by GS8-3 on plant growth.

2.3.4 Measurement of atmospheric CO2 in vitro and analysis its effect on plant growth

Atmospheric CO2 was measured in vitro by using the AnaeroPack MicroAero to identify the

relation of plant growth with CO2 level in vitro. The experiment was performed with 7 % (vol)

CO2 concentration preliminarily kept in the jar with an AnaeroPack MicroAero. In the case of

23

GS8-3 only, the CO2 concentration gradually increased and reached 7 % (vol) to 9 % (vol) in the

jar at seven days of cultivation whereas in the case of tobacco plant only, the CO2 concentration

rapidly decreased after three days and was detected at 1 % (vol) in the jar at seven days after

planting (Fig. 2.5). When tobacco plants were cultivated in the same jar with GS8-3 under

MicroAero, the CO2 concentration gradually decreased to 5 % (vol) after seven days of

cultivation.

The growth of tobacco seedlings were compared between different jars with or without the

fungus and MicroAero condition (Fig. 2.6). Fresh weight (g) of tobacco plants was significantly

increased when cultivated under MicroAero condition compared with the jar without MicroAero.

The highest plant growth was found in the tobacco plants treated with the fungus only which is

similar with the plants cultivated with MicroAero only. Contrastingly, plant growth was found

to be very poor and leaves had become slightly bleached when tobacco plants were treated with

GS8-3 and cultivated under MicroAero condition. Furthermore, the growth of GS8-3 in the jar

with tobacco plants under MicroAero condition seemed poor comparing to that in the jar without

an AnaeroPack MicroAero (Fig. 2. 6).

2.3.5 Extraction and Analysis of volatile metabolites regulated from test fungus

A total of 15 volatile organic compounds were extracted from the PGPF GS8-3 using SPME

coating PDMS/DVB fibers. Among these, 14 were identified as C4-C8 hydrocarbons including

alcohols (2-methyl-propanol, 3-methyl-butanol, 1-hexanol, 2-heptanol, 4-methyl-phenol, phenyl

ethyl alcohol), carboxylic acids (acetic acid, methacrylic acid and tiglic acid), ketones (2-

Hexanone, 2-heptanone, 3-hydroxy-2-butanone/acetoin) and their ester (isobutyl acetate) (Table-

2.1). To investigate the relationship between mould growth and release of fungal volatile

24

substances with time, the volatiles were extracted from different sets of fibers at 3, 5, 7 and 9

days of growth. GS8-3 produced 2-methyl-propanol and 3-methyl-butanol as main volatile

organic components during the culture periods. However, the number and concentration of the

volatiles produced by GS8-3differed with increasing age of the fungus.

2.3.6 Effect of synthetic VOCs on plant growth

Synthetic VOCs that were identified from GS8-3 in 3 and 5 days aged culture individually and

two of their mixtures were tested for their growth promotion effects at four concentrations. In

addition, other two VOCs ( 2,3-butanediol and 1-octen-3-o1) that were previously identified

having growth promotion effect on Arabidopsis by other researchers have also been chosen to

compare their effects on tobacco. Mixture-1 that included the VOCs : 2-methyl-propanol: 3-

methyl-butanol: methacrylic acid: isobutyl acetate (30:60:7:3) extracted from GS8-3 at 3 days

showed 1.4 times significant increase in fresh weight of tobacco over solvent control at 1.8 x10-2

μg concentration (Table-2.2). Besides these, mixture-2 (at 1.8×10-2 μg) that included acetic acid:

2-methyl-porpanol:acetoin: 3-methyl-butanol: methacrylic acid: isobutyl acetate: tiglic acid:

phenylethyl alcohol (14:20:6:46:9:2:2:3) and methacrylic acid (at 1.8×10-4 μg), acetic acid (at

1.8×10-4 μg)and tiglic acid (at 1.8×10-4 μg) individually showed noticeable good effects on

growth promotion though they are not significant. Fresh weight of tobacco was varied in

different concentrations of synthetic VOCs. At high concentration such as at 1.8 and 1.8×102 μg,

most of the compounds caused bleaching of the cotyledon leaves (data not shown).

25

Fig. 2.1. Analysis of growth promotion in tobacco with exposure to airborne chemicals released

from 100 fungal isolates compared with control (PDA only). Representative example of 7 day-

old tobacco seedlings grown on I plates with exposure to airborne fungal isolate (GS8-3) and

PDA only are shown in Inset. I- plates were prepared as gnotobiotic system to avoid

contamination. Figure is showing the fresh weight of tobacco under different treatments with

control ratio as fresh weight of control is 1. Data are the mean of three independent experiments.

26

Fig. 2.2. Growth of tobacco seedlings during 14 days with exposure to airborne chemicals

released form selected fungal isolates compared with PDA alone (blank). There were four

replicates for each treatment and the experiments were repeated three times. Data are the mean of

three independent experiments. Different letters indicate significant differences between

treatments according to Fisher’s LSD at P=0.05

27

Fig. 2.3. Production of CO2 by the selected fungal isolates during 14 days of growth period.

The test fungal isolates were inoculated in a 300 ml Erlenmeyer flask containing 100 ml PDA

and cultured in an incubator set to 12-h-light / 12-h-dark cycle for 7 days at 250 C. Three, 5, 7, 9,

12 and 14 days after inoculations, CO2 concentration was measured by a CO2 detector. Data are

the mean of three independent experiments.

28

Fig. 2. 4. Growth promotion effect of volatile substances of Phoma sp. (GS8-3) in tobacco.

PGPF Phoma sp. (GS8-3) was used as test fungus. Charcoal and silica-gel tube that absorbs

volatiles as soon as they are produced was used to block the flow of volatile compounds toward

the plant flasks were used for comparison. Control treatment was maintained using PDA only

inside the flask without any fungal isolate. Data show fresh weight of tobacco under different

treatments with control ratio as fresh weight of control is 1.Values are means of 3 independent

trails. Different letters on the bars indicate significant differences between treatments according

to Fisher’s LSD at P=0.05.

29

Fig. 2.5. Concentrations of CO2 in vitro under MicroAero condition with or without tobacco

plants and/or Phoma sp. (GS8-3). Three sets of I plates were used in this experiment. In the first

set, 14 days old tobacco seedlings were transferred to MS media and PDA media on the other

side inoculated with Phoma sp. (GS8-3). Second and third sets were prepared with fungus or

plants only. The I plates were placed in the AnaeroPack rectangular jar with 7 % (vol)

preliminary CO2 concentration by an AnaeroPack MicroAero. The jar was placed in growth

cabinets set to a 12-h-light / 12-h-dark cycle for 7 days at 25 oC. There were five replicates for

each treatment and CO2 concentration in the jar was measured by CO2 detector at 1, 3, 5 and 7

days after treatment.

30

Fig. 2.6. Growth promotion of tobacco seedlings with MicroAero condition and/or Phoma sp. (GS8-3).

Tobacco seedlings were grown for 14 days after treatment: from left, the seedlings grew alone (blank),

with Phoma sp. (GS8-3), with Phoma sp. (GS8-3) under microaero condition, or under microaero

condition without Phoma sp. (GS8-3). There were four replicates for each treatment and the experiments

were repeated three times. The data are means of three independent experiments. Bars marked with same

letters are not significantly different according to Fisher’s LSD at P = 0.05.

31

Table 2.1. VOCs extracted from the PGPF isolate Phoma sp. (GS8-3) after 3, 5, 7 and 9 days.

RI = Retention index. Compounds identified base on the comparison of retention index and mass spectra with NIST database.

Compounds RI Peak area (%) 3 days 5 days 7 days 9 days

Acetic acid 0 13.7 0 0

2-Methyl-propanol 621 28.9 19.8 9.4 17.5

3-Hydroxy-2-butanone/ Acetoin 710 0 6.0 0 0

Unknown 713 0 0 0 3.2

3-Methyl-butanol 740 62.1 45.9 83.5 59.6

Methacrylic acid 761 7.0 8.8 0 7.1

Isobutyl acetate 789 2.0 1.5 0 0

2-Hexanone 811 0 0 0 2.1

Octane 801 0 0 0 1.9

Tiglic acid 849 0 1.6 0.4 1.0

1-Hexanol 870 0 0 0 3.6

2-Heptanone 894 0 0 0.4 2.3

2-Heptanol 902 0 0 0.4 0

4-Methyl-phenol 1080 0 0 3.2 0

Phenyl ethyl alcohol 1126 0 2.7 2.7 0

Total 100 100 100 100

32

Table 2.2. Plant growth promotion effect with exposure to volatile organic compounds (VOCs) released from PGPF isolate Phoma sp. (GS8-3) on tobacco.

VOCs Concentration (μg)

1.8×10-4 1.8×10-2

2-Methyl-propanol 1.0 0.9

3-Methyl-butanol 0.9 1.1

Phenyl ethyl alcohol 1.1 1.0

3-Hydroxy-2-butanone 1.0 0.8

2,3- Butanediold 0.9 0.9

1-Octen-3-ole 1.0 1.0

Methacrylic acid 1.2 1.1

Isobutyl acetate 1.0 1.0

Acetic acid 1.2 1.0

Tiglic acid 1.3 1.0

Mixture 1b 1.0 1.4a

Mixture 2c 0.9 1.2

Tobacco seedlings were treated for 14 days with VOCs. Table showed the fresh weight of treated plant with control ratio as the fresh weight of control is 1. a indicted significant different at P <0.05 (LSD).

b is the mixture that duplicated volatiles produced by GS8-3 at 3 day ; 2-methyl-propanol: 3-methyl-butanol: methacrylic acid: isobutyl acetate = 30:60:7:3.

c Mixture -2 is the mixture that duplicated volatiles produced by GS8-3 at 5 day ; acetic acid: 2-methyl-porpanol: 3-hydroxy-2-butanone: 3-methyl-butanol: methacrylic acid: isobutyl acetate: tiglic acid: phenyl ethyl alcohol = 14:20:6:46:9:2:2:3.

d & e, VOCs that were previously reported by other researchers were used to compare the growth promotion effects.

33

2.4 DISCUSSION

We investigated a total of 100 airborne and the soil borne fungal isolates for their growth

promotion effect in tobacco plant and 70 isolates were found to promote plant growth almost

double compared to the control treatment (Fig. 2.1). Among these, randomly selected seven

isolates were rescreened maintaining time course and were found to have significantly higher

growth promotion effect. In this study, we maintained air-tight cultivation using I plates that

restricts physical contact between the fungus and the plant seedlings and allowed only gaseous

exchange. This result suggests that the volatile or gaseous compounds released from the fungal

strains have growth promotion effect on tobacco plants and our result supports the data of Ryu et

al. (2003). These fungi included Phoma sp. GS8-3 which has previously been reported as a

PGPF, as well as a biocontrol agent (Meera et al. 1995; Meera et al. 1994; Shivanna et al. 1995;

Shivanna et al. 2005; Sultana et al. 2009), and was used as a test fungus in the next experiments. In

another test, plant growth was found more than double in the case of GS8-3 treated seedling

without using absorbents comparing to control treatment or the GS8-3 treated plants where

charcoal and silica- gel tube absorbents were used (Fig. 2.4). These materials adsorbed the

volatiles as soon they were produced by the organism and block the transfer of volatiles to the

seedlings. Our method supports the method of Fernando et al. (2005). In this experiment, air-

tight cultivation plates suggesting that the condition of gaseous atmosphere was normalized or

CO2 concentration was elevated through the fungal colony or culture. Thus, CO2 produced by

the fungus inside the chamber might have the possibility of affecting plant growth. Because

many reviews have been published as well on the increased growth of plant species by improved

CO2 supply (Buddendrof-Joosten and Woltering, 1994; Chu et al. 1995; Desjardins, 1995; Pospíšilová et

al. 1992; Sionit et al. 1982). Consequently, in this study we also considered the effect of the

amount of CO2 in vitro during the analysis of the growth promotion effects of PGPF- released

34

volatile metabolites in tobacco. Although previous researchers (Ryu et al. 2003; Yamagiwa et al.

2011) who worked on plant growth promotion effect of VOCs from microorganisms have not

mentioned the involvement of CO2, we located a report (Farag et al. 2006) where considerable

amounts of CO2 were recovered along with the VOCs during profiling of some PGPR. Thus, we

checked the CO2 production by the previously mentioned 7 test fungi until 14 days of culture.

Data showed that among the isolates, D-b-7 and D-c-4 were gradually increasing CO2 production

that indicates positive correlation between the increase of CO2 regulation and growth promotion

of tobacco (Fig. 2.2 and Fig. 2.3). Thus, we assumed that CO2 might play important role of plant

growth promotion effect in case of D-b-7 and D-c-4. But in other isolates including GS8-3, no

such correlation was found as GS8-3 still could increase plant growth significantly in spite of the

decrease in CO2 production after 7 days. Thus, we could distinguish the effect of VOCs in case

Phoma sp. GS8-3 rather than the effect of CO2. Moreover, among the isolates, only the Phoma

spp. have been reported as effective PGPF for many crop species from a detailed study in our

laboratory over years (Hyakumachi and Kubota, 2004) . Therefore, in this work we have chosen

Phoma sp. GS8-3 as a test fungus to analyze the effects VOCs released from this fungus for

better understanding of the growth promotion mechanisms of that PGPF. For further inspection,

we measured the atmospheric CO2 concentration in the presence or absence of GS8-3 and its

effect on plant growth in vitro. We used AnaeroPack MicroAero for CO2 supplement in vitro,

i.e., a non disposable oxygen-absorbing and carbon dioxide-generating agent for use in anaerobic

jar. Result showed that level of CO2 inside the jar was increased when inoculated with GS8-3

with or without plants until 7 days of inoculation (Fig. 2.5). Another set of experiment was done

without using MicroAero and fresh weight of tobacco plants was measured and compared in both

situations at 14 days of planting. Fresh weight (g) of tobacco plants was significantly increased

35

when cultivated under MicroAero condition compared with the jar without MicroAero (Fig. 2.6).

This result supports the findings of Haisel et al. (1999) as they reported that tobacco plantlets

better supplied with CO2 had high net photosynthetic rate, and low transpiration rate and

stomatal conductance. But the highest plant growth was found in the case of tobacco plants

treated with GS8-3 alone in the absence of MicroAero though it was statistically similar with the

plants cultivated with MicroAero only. From the previous experiment (Fig. 2.3) we found that

GS8-3 decreases CO2 production after 7 days of inoculation. This result indicates that aside from

CO2, GS8-3 produce some VOCs that could promote plant growth. Plant growth was notably

poor and leaves became minimally bleached when tobacco plants were treated with GS8-3 and

cultivated under MicroAero condition (Fig. 2.6). In addition, the growth of GS8-3 in that jar

seemed poor compared to that in the jar without an AnaeroPack MicroAero (Fig. 2.6 Inset). It

may be the cause that excess CO2 inhibited the growth of the fungi and changed the gaseous

content inside that chamber by reacting with the VOCs. Previous reports (Burges and Fenton,

1953; Stotzky and Goos, 1965) indicate that higher concentrations (more than 5% increases in

concentration) of CO2 inhibit the growth of microorganisms, especially soil borne fungi. The

altered gaseous atmosphere might be the cause behind growth retardation and bleaching

symptoms of tobacco seedlings. However, the effect of growth promotion on tobacco by GS8-3

alone was higher than that by CO2 supply using MicroAero.

In the next step, we separated the volatile components emitted from GS8-3 at different culture

periods by gas chromatography, and identified by mass spectrometry. Identified VOCs belonged

mostly to four classes of C4-C8 hydrocarbons where 2-methayl-propanol and 3-methayl-butanol

were mostly found in considerable concentrations for all the fungal age (Table-2.1). Compounds

of these characteristic metabolites were detected as indicator substances for mould growth

36

(Börjessonet al. 1992). These two components were previously extracted from some PGPR (Farag

et al. 2006). Volatiles were found variable in number and amount by the age of fungus. Among

the identified VOCs, acetoin (3-hydroxy-2-butanone) was discussed in many reports (Farag et al.

2006; Ryu et al. 2003; Ryu et al. 2004) for their growth promoting and ISR triggering ability in

Arabidopsis when released from PGPR. We opted to analyze all the VOCs extracted at 3 days

and 5 days of GS8-3 culture for the growth promotion effect, as the rest of the compounds have

been found in trace amounts. Aside from these, 2,3-butanediol (Ryu et al. 2003) , and 1-octen-

3-o1 (Kishimoto et al. 2007; Meruva et al. 2004; Schnurer et al. 1999) have also been checked in

tobacco as these two metabolites were previously reported to promote growth and to induce

defense response in Arabidopsis. Synthetic VOCs and their mixtures were performed at four

concentrations. Mixture -1 (2-methyl-propanol: 3-methyl-butanol: methacrylic acid: isobutyl

acetate in 30:60:7:3 ratio respectively) showed greatest level of growth promotion (1.4 times)

compared to control (Table-2.2). Mixture -2 (acetic acid: 2-methyl-porpanol: acetoin: 3-methyl-

butanol: methacrylic acid: isobutyl acetate: tiglic acid: phenylethyl alcohol in 14:20:6:46:9:2:2:3

ratio respectively) also showed better result than control. This supports the findings of Ryu et

al. (2003), that better growth promotion effect is seen from all VOC blends. Though the VOCs

did not show individual growth promotion effect significantly, few of them like methacrylic acid,

acetic acid and tiglic acid still show good control ratio. Yamagiwa et al. (2011) also reported

similar level of growth promotion effect of the volatile β-caryophyllene in turnip. However,

we failed to notice a positive effect of 2, 3-butanediol and 1-octen-3-o1 in tobacco. Probably, the

growth stimulating ability of VOCs differ according to plant species. As the fresh weight of

tobacco plants varied at different concentrations of synthetic VOCs, from our observations,

VOCs at lower concentrations showed better growth promotion than at higher concentrations.

37

Previously, we have mentioned that plant growth promoting microorganisms promote plant

growth by producing growth regulating hormones (Loper and Schroth, 1986; MacDonald et

al.1986; Timmusk et al. 1999), mineralizing nutrient substrates (Hyakumachi and Kubota, 2004.)

and suppressing deleterious microorganisms (Farag et al. 2006; Kishimoto et al. 2007; Ryu et al.

2004). Ryu et al. (2003) revealed the possible involvement of PGPR regulated VOCs in the

growth regulatory signaling pathways by using different mutant plants. They also speculated the

possibility of using PGPR VOCs in other cultivation methods other than air-tight cultivation. We

have also analyzed the growth promotion effects of PGPF produced VOCs in open air-

cultivation system. But in our case, VOCs were not found as effective growth inducer in open-air

system (data not shown).In this report, we have tried to find out the potential role of PGPF

regulated VOCs in the orchestra of growth regulatory mechanisms. We found that Phoma sp.

GS8-3 could induce growth promotion in tobacco in airtight cultivation system that suggests it’s

contemporary participation in the growth promotion effect of plant growth promoting fungi.

However, the involvement of PGPF released VOCs in the growth regulatory signaling pathways

remains to be determined.

38

CHAPTER 3

Systemic resistance induced by volatile organic compounds emitted by plant growth-promoting fungi in Arabidopsis

thaliana

39

Systemic resistance induced by volatile organic compounds emitted by plant growth-promoting fungi in Arabidopsis thaliana

3.1 INTRODUCTION

Non-pathogenic, filamentous, saprophytic rhizosphere fungi that significantly enhance the

growth of plants are known as plant growth-promoting fungi (PGPF) (Hyakumachi, 1994;

Shivanna et al. 1994). In the search for alternate disease control strategies to minimize the use of

chemical pesticides, the discovery of PGPF brought new expectations to researchers worldwide.

In the past few years, PGPF from the genera of Fusarium, Penicillium, Phoma, and Trichoderma

have been frequently studied and evaluated for their high suppressive abilities against a variety

of plant diseases as a result of direct antagonism against soil-borne pathogens or by inducing

systemic resistance in the plant (Ahmad and Baker, 1988; Shivanna et al. 1996; Shivanna et al.

2005; Hossain et al. 2007; Yoshioka et al. 2012). PGPF have been extensively studied to

elucidate the mechanisms underlying the disease suppressiveness using different forms of

inocula such as barley grain inocula or cell free culture filtrates (Hossain et al. 2007; Yoshioka et

al. 2012; Koike et al. 2011; Meera et al. 1994). Molecular characterizations of the mechanism of the

disease suppressive effects of PGPF or its culture filtrate proved that multiple signaling pathways

are involved in ISR by PGPF and are mainly mediated by SA/JA-ET signals (Hossain et al.

2007; Yoshioka et al. 2012; Sultana et al. 2008).

Recent studies have also revealed that volatile organic compounds (VOC) released from some

PGPF strains can effectively promote plant growth and enhance disease resistance (Yamagiwa et

al. 2011; Naznin et al. 2013). In our previous study, we screened about 100 fungal strains by

growing them in sealed I-plates (containing a center partition) with tobacco seedlings but without

40

physical contact between the strain and seedling; most plants increased growth when exposed to

the volatile substances of the fungi. The volatile blends isolated from Phoma sp. GS8-3

significantly increased plant growth at low concentrations (Naznin et al. 2013). Yamagiwa et al.

(2011) reported that the volatile compound β-caryophyllene emitted from the PGPF Talaromyces

wortmannii FS2 significantly enhanced the growth of komatsuna (Brassica campestris L. var.

perviridis) seedlings and their resistance to Colletotrichum higginsianum. Although reports on

VOC from PGPF are relatively recent and few in number, the role of volatiles emitted from

plants and other microorganisms on plant development have been studied extensively (Farmer,

2001; Ryu et al. 2004).

Many reports have focused on the effects of volatiles produced by rhizobacteria or plant growth

promoting rhizobacteria on plant disease control. Several volatiles produced by rhizobacteria

have exhibited antibacterial or antifungal activities (Kai et al. 2009). Two volatiles, 2,3-

butanediol and acetoin (3-hydroxy-2 butanone), produced by Bacillus subtilis and Bacillus

amyloliquefaciens have been identified as important factors in inducing systemic resistance and

promoting plant growth (Ryu et al. 2004; Farag et al. 2006). Volatiles produced by a few strains

of Streptomyces are also reported to have potential for biocontrol (Wan et al. 2008; Li et al.

2010).

While most studies have focused on the interaction between rhizobacteria and plant pathogens,

little is known about the plant response to VOC emitted by PGPF and the resistance that is

conferred. Therefore, in the present study, we aimed to establish whether the PGPF-released

VOC can induce systemic resistance in plants, and if they can, to determine what types of

signaling pathways are involved in this ISR. We isolated the VOC from different PGPF and

examined the disease suppression efficacy of VOC in a hydroponic culture system using the

41

model plant Arabidopsis thaliana (Arabidopsis) and bacterial leaf speck pathogen Pseudomonas

syringae pv. tomato DC3000 (Pst) and explicated the molecular basis of VOC-induced ISR in

Arabidopsis.

42

3.2 MATERIALS AND METHODS

3.2.1 PGPF isolates

Fungal isolates Cladosporium sp. (D-c-4), Ampelomyces sp. (D-b-7, F-a-3) and Phoma sp. (GS8-

3) used for VOC analysis were collected and identified at the laboratory of Plant Pathology, Gifu

Univerisity.

3.2.2 Test plants and pathogen

Seeds of Arabidopsis thaliana ecotype Columbia (Col-0) were provided by Dr. K.S. Park

(NIAST, Suwon, Korea). Mutants ein3 (Chao et al. 1997), npr1 (Cao et al. 1994) and jar1

(Staswick et al. 1992) were obtained from NASC (The Nottingham Arabidopsis Stock Centre) and

transgenic line NahG was a personal gift (Lawton et al. 1995). All the mutants and transgenic

Arabidopsis lines were developed against the background of the Col-0 ecotype. Virulent

pathogen Pseudomonas syringae pv. tomato (pst) DC3000 was provided by Y. Ichinose

(Okayama University, Okayama, Japan).

3.2.3 Extraction and analysis of volatile metabolites from PGPF isolates

Three PGPF isolates were cultured in 10 mL solid phase micro extraction (SPME) vials

(Supelco, Sigma-Aldrich Co. US), and the volatile metabolites were extracted by headspace

SPME during 30 min at 25 C. Polydimethylsiloxane/divinylbenzene (PDMS/DVB) (65 μm)

fibers were used for volatile profiling. Fibers were obtained from Supelco and conditioned before

analyses according to the manufacturer’s recommendations. The composition of VOC 1, VOC 2

and VOC 3, isolated from Phoma sp. (GS8-3), Ampelomyces sp. (F-a-3) and Cladosporium sp.

(D-c-4), respectively, were identified using GC-MS analysis as described by Miyazawa et al.

(2008). Compounds were identified using the U.S. National Institute of Standards and

43

Technology (NIST) Mass Spectral Library or by comparing the retention times and spectra with

those of authentic standards and Kovats retention indices with literature data.

3.2.4 Hydroponic culture of plants

Arabidopsis plants were grown in a hydroponic culture system developed by Toda et al. (1999).

In this system, seeds were sown on nylon mesh (50 holes per inch) and were placed in a plastic

photo-slide mount (50 x 50 mm; Fuji film, Japan). These mesh mounts were floated in a plastic

case with the help of small pieces of styrofoam on 5 L of 1:10 MGRL nutrient solution (pH 5.6)

and kept in a growth chamber at 24oC with a 12 h day/12 h night cycle (Fujiwara et al. 1992). The

nutrient solution was renewed every 7 days, and the culture was continued for 2 weeks.

3.2.5 Application of Volatile organic compounds (VOC)

The volatile compounds, VOC 1, VOC 2, and VOC 3 (Table 3.1) that were identified through

GC-MS analysis and commercial methacrylic acid and isobutyl acetate (synthetic chemicals)

were dissolved in CH2Cl2 and diluted to a 0.1 M solution. VOC were mixed with 0.1 g of lanolin

before use and then 50 μL of one of the VOC was applied to a sterile paper disk and kept on a

glass petri dish (3 cm). A dilution series (1 μM to 100 mM) of m-cresol and MeBA was also

prepared and used to analyze dose-specific effects on disease severity. Hydroponically grown,

13-d-old Arabidopsis plants were transferred to a medium-sized (13 x 32 x 18.5 cm) plastic case

containing 1/10 MGRL and kept in a large plastic case with the VOC in the glass petri dish. The

whole system was then covered quickly and held for 24 h before inoculation with the pathogen.

3.2.6 Inoculation

44

The virulent bacterium Pst DC3000 was cultured in Kings’ B broth containing rifampicin (50

mg/L) for 2 days at 28 C. The bacterial cells were collected by centrifugation, washed twice with

sterilized distilled water (SDW) and resuspended in SDW to a final concentration of 7.0 x 107–

8.0 x 107 colony forming units (cfu)/mL (OD600 = 0.070–0.080). The surfactant Silwet L-77

(0.01% v/v; Nihon Unica, Tokyo, Japan) was added as a spreading agent during inoculation. One

day after the VOC treatment, 2-wk-old plants were sprayed with 200 mL of bacterial suspension.

The inoculated plants were then kept at 100% relative humidity in the dark for 2 days to induce

disease development. Plants were then transferred to the growth chamber with 12 h day/12 h

night cycle and held for 3 more days.

3.2.7 Assessment of disease severity

Five days after the pathogen challenge, disease severity was scored, and the number of colony

forming units of Pst (cfu)/g of leaves was determined for 10 randomly selected plants. Severity

was scored for each plant as the percentage of total leaf surface with symptoms, from 0 = no

symptoms to 100 = most severe with necrotic symptoms, and calculated using the formula

described by Hossain et al. (2007). To determine the number of Pst DC3000 cells in inoculated

leaves, we collected and weighed all leaves from the samples, rinsed them thoroughly in sterile

water, then homogenized them in sterilized distilled water. Leaf suspensions were plated on KB

agar supplemented with rifampicin (50 mg/L), and after 48 h incubation at 28 C, the number of

cfu of Pst per gram of leaves was calculated. The experiment was repeated 3 times.

3.2.8 RT-PCR analysis

After the 24-h VOC treatment, aerial parts from 15 randomly selected plants were sampled in 1.5

mL Eppendorf tubes, ground in liquid nitrogen and homogenized with 600 μL of the extraction

45

buffer (20 g of guanidine thiocyanate, 0.2 g of N-lauroylsarcosine sodium salt and 0.2 g of

trisodium citrate dihydrate dissolved in 40 mL of RNase free water) and 10 μL of 2-

mercaptoethanol. The aqueous phase resulting from centrifugation at room temperature was re-

extracted with a phenol : chloroform : isoamyl alcohol (PCI) (25 : 24 : 1; v/v) mixture. The upper

aqueous phase was precipitated with isopropanol followed by a 75% ethanol rinse. The

precipitated RNA was collected, air-dried briefly and dissolved in RNase-free water. After

treatment with RNase-free DNase and inactivation of the DNase according to the instructions of

the supplier (Takara Bio, Shiga, Japan), approximately 1 μg of total RNA was reverse

transcribed to single-strand cDNA, and a sample of the obtained cDNA was amplified by RT-

PCR, as described by Suzuki et al. (2004) to analyze the expression of a set of well-characterized

defense-related genes. The expression of candidate priming gene was analyzed using the

following primers: F-5 -GTAGGTGCTCTTGTTCTTCC-3 , R- 5 -

TTCACATAATTCCCACGAGG-3 (PR-1;At2G14610, product size 421 bp) and F-5 -

AATGAGCTCTCATGGCTAAGTTTGCTTCC-3 ), R-5 -

AATCCATGGAATACACACGATTTAGCACC-3 (PDF1.2a; At5G44420, product size 281

bp). Expression of defense-related genes was determined by semi-quantitative RT-PCR. PCR

products were separated on a 1.5% agarose gel, and intensities of bands were scanned with

Typhoon 9400 Variable Mode Imager (GE Healthcare UK, Amersham, UK). The signal strength

of each band was expressed numerically with the program image Quant 5.2 (GE Healthcare), and

the relative expression level of each gene was calculated. β-tublin (TUB8; AT5G23860) was

used as an internal standard using primers Forward-5 -CGTGGATCACAGCAATACA-3 and

Reverse-5 -CCTCCTGCACTTCCACTT-3 .

3.2.9 Real-time quantitative RT-PCR analysis

46

Real-time RT-PCR assay was performed using real-time PCR, ABI PRISM 7000 system

(Applied Biosystems, Tokyo, Japan) using the default thermocycler program for all genes.

Approximately 1 μg of total RNA was reverse transcribed to single-strand cDNA as described by

Suzuki et al. (2004) after inactivation of DNase I according to the manufacturer’s instructions

(Takara Bio, Shiga, Japan). A sample of the obtained cDNA was amplified to monitor the

expression of a set of selected genes. Power SYBR Green Master Mix was used according to the

manufacturer’s instruction; 1 μL of cDNA to 10 μL of SYBR Green Master mix: 0.8 μL of 5 μM

primer F&R: 7.4 μL SDW. Primers used for real-time PCR are listed in Table 3.2. The relative

signal intensity compared with control plants was calculated using 2 ΔΔCt from the threshold

cycle (Ct) values according to the manufacturer’s software. Relative RNA levels were calibrated

and normalized against expression levels of the internal control genes UBQ5 and ACT2.

3.2.10 Statistical analysis

The experimental design was completely randomized, consisting of three replications for all

treatments. The experiment was repeated at least twice. Data were subjected to analysis of

variance (ANOVA), and a Student’s t-test was used to determine statistically significant

differences between treated samples and untreated control.

47

3.3 RESULTS

3.3.1 Extraction and identification of volatile metabolites from PGPF isolates

When the volatile metabolites were extracted from 2-wk-old cultures of three PGPF isolates

using headspace SPME and identified using gas chromatography–mass spectrometry (GC-MS),

most of the VOC from Phoma sp. (isolate GS8-3, VOC 1) and Ampelomyces sp. (isolate F-a-3,

VOC 2) were C4–C8 hydrocarbons (Table 3.1). VOC 1 comprised 2-methyl-propanol (9.4%), 3-

methyl-butanol (83.8 %), 2-heptanone (0.4%), 2-heptanol (0.4%), 4-methyl-phenol (3.3%) and

phenylethyl alcohol (2.8%). VOC 2 comprised 2-methyl-propanol (3%), 3-methyl-butanol (22.6

%), 4-heptanone (2.5%), 3-octanone (1.1%), m-methyl-anisole (1.9%), m-cresol (59.8%),

phenylethyl alcohol (8.6%) and cubenene (0.6%). Only one volatile component, methyl benzoate

(MeBA) (100%), was identified from Cladosporium sp. (isolate D-c-4, VOC 3).

3.3.2 VOC emitted from PGPFs suppress disease severity

Arabidopsis plants were treated with one of the volatile organic compounds (VOC 1, VOC 2 or

VOC 3) isolated from the 3 PGPFs in hydroponic culture (Table 3.1). After 24 h of treatment,

plants were inoculated with bacterial leaf speck pathogen P. syringae pv. tomato (Pst) DC3000,

and disease symptoms and number of bacteria were evaluated 5 days after inoculation. As shown

in Fig. 3.1 (A, B), Arabidopsis Col-0 plants treated with VOC 2 (Ampelomyces sp. F-a-3) and

VOC 3 (Cladosporium sp. D-c-4) resulted in a significant reduction in disease severity compared

with the control. Disease severity, based on an index for percentage of total leaf surface with

symptoms then calculated as the percentage protection compared with the control, in Arabidopsis

plants was 39% after treatment with VOC 2 and 34% with VOC 3 (MeBA). On the other hand,

disease severity in plants treated with VOC 1 isolated from Phoma sp. (GS8-3) was higher than

48

in the control. Results in Fig. 3. 1(C) present the number of colony-forming units (cfu g-1) of P.

syringae pv. tomato (Pst) DC 3000 in challenged leaves and reveal that the plants treated with

VOC 2 and VOC 3 caused an approximately 2.4- and 3.8-fold decrease in cfu g-1, respectively,

compared with the control.

3.3.3 VOC induced high expression of defense-related genes

To evaluate the roles of SA and JA in the VOC-induced defense responses in Arabdiposis, the

expression of SA- and JA-dependent marker genes was analysed by semi-quantitative PCR (Fig.

3.2. A and B). The expression level of the SA-inducible gene PR-1 and of JA-inducible gene

PDF 1.2 was significantly higher in aerial parts of Arabidopsis treated with VOC 2 and VOC 3

(MeBA) than in the control. On the other hand, VOC 1-treated plants did not express defense-

responsive genes. Expression of PR-1 was 2 and 2.5 times higher than in the control in VOC 2-

and VOC 3 (MeBA)-treated plants, respectively. PDF 1.2 was expressed 3.9 and 2.6 times

higher in VOC 2- and VOC 3 (MeBA)-treated plants, respectively, over the control. Thus, both

SA- and JA-signalling are involved in the VOC-induced defence in Arabidopsis.

Because MeBA was identified as the major (100%) volatile compound in VOC 3 emitted by

Cladosporium sp. D-c-4 that elicits ISR (Figs. 3.1, 3.2), while VOC 2 was extracted as a blend of

volatiles (Table 3.1), we further analyzed VOC 2 to identify the major active volatile compound

emitted by Ampelomyces sp. F-a-3.

3.3.4 m-Cresol is a major component with an important role in disease supression by

Ampelomyces sp.

As we see in Figs. 3.1 and 3.2, VOC 2 (blend of volatiles) from Ampelomyces sp. and VOC 3

(MeBA) from Cladosporium sp. significantly suppressed disease against Pst DC3000. In the

49

blend of volatiles produced by Ampelomyces sp. F-a-3, m-cresol occupied the leading position

(59.8%). Therefore, in the next step, we analysed all the components extracted from

Ampelomyces sp. for their ability to reduce disease and the pathogen population. Together with

the F-a-3 volatiles, 2 of the VOC, methacrylic acid and isobutyl acetate, found to be common

components in 3- and 5-d-old cultures of Phoma sp. GS8-3 in our previous study (Naznin et al.

2013), were also included in the ISR test. Fig.3.3 shows that 3 of the VOC from Ampelomyces

sp. (F-a-3), 3-octanone, m-cresol, phenyl ethyl alcohol, and the test volatiles methacrylic acid

and isobutyl acetate induced systemic resistance in Arabidopsis against Pst DC3000 by 5 days

after inoculation. Among the VOC, 3-octanone was highly effective in disease supression, and

the bacterial population was reduced the most by treatment with m-cresol. From 14-d cultures, 3-

octanone was identified as a trace component (1.1%), whereas m-cresol was greatest (59.8%) in

the total volatile blend. We thus considered this compound to be the major active volatile

component involved in the ISR by Ampelomyces sp. F-a-3.

3.3.5 Dose-specific effects of m-cresol and MeBA on ISR

To observe the effects of m-creosl and MeBA on ISR at different concentrations, we pretreated

plants with a dilution series of the compounds (1 μM to 100 mM) before pathogen inoculation,

then scored the percentage disease severity and the pathogen population. As we see in Fig.3.4,

both m-cresol and MeBA induced ISR at all concentrations. Although the effect varied at

different concentrations of m-cresol and MeBA, they both reduced disease severity more at the

higher concentrations in the case of both VOC, and the pathogen population was decreased the

50

most at 100 mM. However, m-cresol and MeBA both induced ISR significantly over the control

even at low concentrations.

3.3.6 Systemic resistance induced by methyl benzoate is compromised in Arabidopsis

genotypes defective in JA-dependent signalling pathway

Previously, we checked the induction of defense-related genes PR-1 and PDF-1.2 in Arabidopsis

plants treated with VOC blends (Fig. 3.2). To elucidate the signalling pathways leading to the

ISR mediated by the major VOC, we exposed different Arabidopsis mutants or transgenic plants

that are impaired in a specific regulatory pathway to the major VOC that triggered ISR: SA-

deficient mutant npr1, impaired in NPR1 activity or nonexpressor of PR genes; Arabidopsis

transgenic plant NahG, defective in SA-dependent signalling; an ethylene-insensitive3 (ein3)

mutant and a JA-deficient mutant jar1. Application of methyl benzoate (MeBA) extracted from

Cladosporium sp. D-c-4 significantly decreased development of leaf specks caused by Pst

DC3000 in the npr1 mutant, impaired in NPR1 activity and in the ein3 mutant, impaired in ET-

dependent signalling (Fig. 3.5 A). Bacterial growth also followed a trend similar to lesion

development in npr1 and ein3 (Fig. 3.5 B), indicating that ISR mediated by MeBA is

independent of SA and ET signalling. On the other hand, disease severity and the pathogen

population were higher in the JA-signalling defective jar1 mutant implicating the involvement of

JA-signalling pathways in ISR by MeBA. Remarkably, disease severity in Arabidopsis

transgenic plant NahG was not signficantly reduced by treatment with MeBA, albeit the bacterial

population was significantly lower than in the control. This result indicates a partial recriutment

of the signal transduction molecule SA in MeBA-mediated ISR.

51

3.3.7 m-Cresol failed to induce systemic resistance in Arabidopsis mutants impaired in SA-

/JA-dependent signalling pathways

m-Cresol was also tested to determine the molecular patterns of induced systemic resistance in

Arabidopsis plants using the same set of genotypes as those used in the MeBA treatment. Results

showed that the percentage protection and the reduction of bacterial population were

compromised in the SA-signalling-defective transgenic plant NahG, the NPR1-activity-impaired

mutant npr1, and the JA- signalling-impaired mutants jar1 plants treated with m-cresol (Fig. 3.5.

C&D). On the other hand, lesion development and proliferation of bacterial pathogens in ET-

signalling-impaired Arabidopsis mutant plants were significantly reduced in contrast to the

control. These results indicate that the SA-signalling pathway is essential for m-cresol-induced

systemic resistance in Arabidopsis plants, including partial JA-signalling.

3.3.8 Induction of Arabidopsis defense-related genes in plants treated with major VOC,

MeBA and m-cresol

To define more clearly the role of SA-, JA- and ET-signal transduction pathways in the induction

of systemic resistance by VOC, we further studied the induction pattern of marker genes for

these pathways in plants exposed to the major VOC (Table 3.2). Plants were treated with VOC

for 24 h, and transcription of SA-inducible gene PR1, PR2, PR5 and ET-inducible gene PR4, JA-

/ET-inducible gene PR3, PDF1.2 and JA-inducible AtVSP2 and MYC2 was analysed by real-

time quantitative RT-PCR. Result showed that relative expression of SA-inducible gene PR1 and

PR2 was significantly higher (more than 6-fold and 2.5-fold, respectively) in m-cresol-treated

plants (Fig. 3.6). PR1 also showed high expression after the MeBA treatment (>2 fold),

supporting the previous data on SA involvement (Fig. 3.2). On the other hand, JA/ET-inducible

52

marker gene PDF1.2, JA-inducible gene MYC2, and VSP2 showed significantly higher relative

expression in case of MeBA-treated plants. m-Cresol also significantly induced the JA/ET-

inducible gene PDF1.2 (>2 fold), strengthening support for the involvement of JA based on the

previous data (Figs. 3.2, 3.5). The expression of ET-inducible marker gene PR4 was also higher

(>1.6 fold) after m-cresol treatment, differing from the data in Fig. 3.5, but not after the MeBA

treatment. The JA/ET-inducible gene PR3 and SA-inducible marker gene PR5 were not

noticeably expressed in our experiments.

53

Fig. 3.1. Suppression of disease symptoms and numbers of Pst DC3000 after VOC

pretreatment in Arabidopsis thaliana. A. Plants (17-d-old) on mesh screen in a slide mount 5

days after challenge inoculation with Pst DC3000. Plants were treated with VOC1 (Phoma sp.

GS8-3), VOC2 (Ampelomyces sp. F-a-3) and VOC 3 (Cladosporium sp. D-c-4) for 24 h then

inoculated with Pst. VOC1 and VOC2 were used as blend of volatiles; VOC3 was methyl

benzoate (MeBA) only. Control was treated with CH2Cl2 only; MeSA and MeJA were used as

positive controls. B. VOC-induced reduction of disease severity. Severity was scored for each

plant as the percentage of total leaf surface with symptoms, from 0 = no symptoms to 100 =

most severe with necrotic symptoms. C. Growth of Pst DC3000 (cfu g-1 fresh mass) in leaves.

Asterisks indicate values differ significantly (Student’s t-test, P = 0.01) from the control. Data are

from representative experiments that were repeated at least 3 times with similar results.

54

Fig. 3.2. Expression of of defense-related genes. A. SA-responsive gene PR-1 and B. JA-

responsive gene PDF 1.2 in leaves of Arabidopsis thaliana treated with VOC 1, VOC 2 or VOC

3 (MeBA) of PGPFs in semi-quantitative RT-PCR analysis. Asterisks indicate statistically

significant differences (Student’s t-test, P = 0.01) compared with the control. Data are from

representative experiments that were repeated at least 3 times with similar results.

55

Fig. 3.3. Supression of disease symptoms and pathogen population by VOC isolated

from Ampelomyces sp. A. VOC-induced reduction of disease severity caused by Pst DC3000

in Arabidopsis. Severity was scored for each plant as the percentage of total leaf surface with

symptoms, from 0 = no symptoms to 100 = most severe with necrotic symptoms. B. Growth of

Pst DC3000 (cfu g-1 fresh mass) in leaves. Plants were pretreated with 50 μL of one of the

volatile components (0.1 M) for 24 h before inoculation. Methacrylic acid and isobutyl acetate

were also tested as volatiles. Controls received only CH2Cl2; MeSA and MeJA were used as

positive control treatments. Asterisks indicate statistically significant differences (Student’s t-

test, P = 0.01) compared with the control. Data are from representative experiments that were

repeated at least 3 times with similar results.

56

Fig. 3.4. Systemic resistance induced by m-cresol and methyl benzoate (MeBA) at

different concentrations. A. Reduction in disease severity and B. Growth of Pst DC3000 in

leaves after pretreatment of plants with m-cresol and MeBA at different concentrations followed

by challenge inoculation with Pst DC3000. Disease severity was scored for each plant as the

percentage of total leaf surface with symptoms, from 0 = no symptoms to 100 = most severe,

with necrotic symptoms. Asterisks indicate statistically significant differences (Student’s t-test, P

= 0.01) compared with the control. Data are from representative experiments that were repeated

at least 3 times with similar results.

57

Fig. 3.5. Suppression of disease symptoms and Pst DC3000 population by VOC methyl

benzoate (MeBA) and m-cresol. Arabidopsis transgenic plants and mutants impaired in defense

signalling pathways and wild-type (Col-0) plants were used. A. Reduction in disease severity and

B. Growth of Pst DC3000 in leaves after MeBA pretreatment followed by challenge inoculation

with Pst DC3000. C. Reduction in disease severity and D. Growth of Pst DC3000 in leaves after

m-cresol pretreatment followed by challenge inoculation with Pst DC3000. Data are percentage

of disease severity (scored for each plant as the percentage of total leaf surface with symptoms,

from 0 = no symptoms to 100 = most severe with necrotic symptoms) or number of cfu g-1 fresh

mass 5 days after challenge inoculation. Asterisks indicate statistically significant differences

(Student’s t-test, P = 0.01) compared with the control. Data are from representative experiments

that were repeated at least 3 times with similar results.

58

Fig. 3.6. Relative expression of defense-related genes on leaves of A. thaliana treated with

m-cresol and MeBA. Amplification of JA-/ET-responsive genes PR3 and PDF1.2, JA-

responsive genes AtVSP2 and MYC2, ET-responsive gene PR4, and SA-inducible genes PR1,

PR2 and PR5 were analyzed with real-time qRT-PCR. Leaves from 15 representative plants

were sampled 5 days after inoculation. Asterisks indicate statistically significant differences

(Student’s t-test, P = 0.01) compared with the control treatment.

59

Table 3.1: Retention index (RI) and peak areas for volatile organic compounds (VOC) extracted

from 14-d-old cultures of the plant-growth-promoting fungi Phoma sp. (GS8-3), Ampelomyces

sp. (F-a-3) and Cladosporium sp. (D-c-4) using SPME-based GC-MS analysis.

Peak areas (%)

Compounds RI VOC 1

(Phoma sp. GS8-3)

VOC 2

(Ampelomyces sp. F-a-3)

VOC 3

(Cladosporium sp. D-c-4)

2-Methyl-propanol 9.4 3.0 -

3-Methyl-butanol 83.8 22.6 -

4-Heptanone - 2.5 -

2-Heptanone 0.4 - -

2-Heptanol 0.4 - -

3-Octanone 986 - 1.1 -

m-Methyl-anisole 1022 - 1.9 -

4-Methyl-phenol 1080 3.3 -

m-Cresol 1081 - 59.8 -

Methyl benzoate 1095 - - 100.0

Phenylethyl alcohol 1116 2.8 86 -

Cubenene 1376 - 0.6 -

Total 100.0 100.0 100.0

Note: Compounds were identified by comparing the RI and mass spectra with data in the NIST

database.

60

Table 3. 2: Gene-specific primers used in real-time qRT-PCR analysis

AGI code Target

gene

Primer sequences Product size

(bp)

Salicylic acid regulated gene

At2g14610

PR-1 F5 -TTCTTCCCTCGAAAGCTCAA-3

R 5 -AAGGCCCACCAGAGTGTATG-3

174

At3g57260 PR-2 F 5 -AGCTTAGCCTCACCACCAATGT-3

R 5 -CCGATTTGTCCAGCTGTGTG-3

83

At1g75040

PR-5 F 5 - TGTTCATCACAAGCGGCATT-3

R5 GTCCTTGACCGGCGAGAGTTAATGCCGC-3

99

Jasmonic acid / Ethylene regulated gene

At3g12500

PR-3 F 5 -GGCCAGACTTCCCATGAAAC-3

R 5 -CTTGAAACAGTAGCCCCATGAA-3

113

At3g04720 PR-4 F 5 -GCAAGTGTTTAAGGGTGAAGAACA-3

R 5 -GAACATTGCTACATCCAAATCCAAG-3

104

At5g44420

PDF1.2 F 5 -TTTGCTGCTTTCGACGCAC-3

F 5 -CGCAAACCCCTGACCATG-3

80

At5g24770

AtVSP2 F 5 -TCAGTGACCGTTGGAAGTTGTG-3

R 5 -GTTCGAACCATTAGGCTTCAATATG-3

104

At1g32460 MYC2 F 5 -AGCAACGTTTACAAGCTTTGATTG-3

R 5 -TCATACGACGGTTGCCAGAA-3

76

Housekeeping gene / internal control

At3g62250

UBQ5 F 5 -GACGCTTCATCTCGTCC-3

R 5 -GTAAACGTAGGTGAGTCCA-3

256

At2g37620 ACT2 F 5 -AGTGGTCGTACAACCGGTATTGT-3

R 5 -GATGGCATGAGGAAGAGAGAAAC-3

92

61

3.4 DISCUSSION

In our previous study, we validated that chemical signals were being emitted into the air from the

fungi Phoma sp. (GS8-3), Ampelomyces sp. (F-a-3) and Cladosporium sp. (D-c-4) and

contributed to promoting the growth of tobacco seedlings (Naznin et al. 2013). Here, we isolated

the VOC from these PGPF and analyzed their potential for plant protection by pretreating

Arabidopsis plants and challenging them with the pathogen Pseudomonas syringae pv. tomato

DC3000 (Pst). Protection of the plant was manifested by both a reduction in disease severity and

a decrease in pathogen proliferation in the leaves. The VOC emitted from the PGPF suppressed

Pst infection via induced systemic resistance since there was less disease without direct contact

between the VOC and the pathogen. Phoma sp. (GS8-3) and Ampelomyces sp. (F-a-3) emitted a

blend of volatile components, whereas only one volatile (MeBA) was produced by

Cladosporium sp. (D-c-4) after 14 days of culture (Table 3.1). Different strains of Phoma sp.

including GS8-3 have previously been reported to promote growth and induce systemic

resistance in plants (Chandanie et al. 2006; Sultana et al. 2009). In addition, we found that a

volatile blend emitted by GS8-3 was able to increase plant growth (Naznin et al. 2013). But

unexpectedly, in the present study, the VOC isolated from plants treated with Phoma sp. (GS8-3)

did not suppress disease or reduce the pathogen population after inoculation with the pathogen

(Fig. 3.1). On the other hand, volatile components isolated from Ampelomyces sp. (F-a-3) and

Cladosporium sp. (D-c-4) did reduce disease symptoms and pathogen population significantly,

as did the positive control treated with MeJA and MeSA. The mycoparasite Ampelomyces

quisqualis, a well-known biocontrol agent, is widely used for controlling powdery mildew of

different plants and is known to act by hyperparasitism (Elad et al. 1998; Gilardi et al. 2008), but

our finding that Ampelomyces sp. emits VOC that can induce systemic resistance is undisputedly

62

the first report for this antagonist. Likewise, Cladosporium spp. is also a mycoparasite of

powdery mildew fungi (Kiss, 2003), parasitizing the surface of the penicillate cells of the

cleistothecia and causing plasmolysis of the conidia (Kiss, 2003; Mathur and Mukerji, 1981).

Antifungal compounds were presumed to play role in this inhibitory effect or antibiosis, but the

mode of action had not been studied in detail.

In the present study, we isolated a volatile compound from Cladosporium sp. (D-c-4) that could

induce systemic resistance in plants. In addition, to determine the mode of action underlying the

ISR by the VOC extracted from the PGPF strains, we checked two Arabidopsis defense-related

genes PR-1 (SA) and PDF1.2 (JA/ET) for post-inoculation amplification. Our results showed

that disease suppression by the VOC isolated from both F-a-3 and D-c-4 involved the SA and

JA/ET pathways (Fig. 3.1 B), with methyl benzoate (C6H5CO2CH3) the only compound (100%)

emitted by Cladosporium sp. (D-c-4). In the mixture of VOC emitted by Ampelomyces sp. (F-a-

3), m-cresol (CH3C6H4OH) significantly induced systemic resistance and was the most abundant

of all the VOC, confirming it as the major active volatile compound in ISR (Fig. 3.3).

Methacrylic acid and isobutyl acetate, were isolated as common components from Phoma sp.

GS8-3 after 3 and 5 days of culture in our previous study (Naznin et al. 2013), so we included

them in ISR tests. Because the volatiles varied in number and quantity over time during culture

(Naznin et al. 2013), we isolated VOC from a 14-d-old fungal culture, when methacrylic acid

and isobutyl acetate are absent from the VOC profile of Phoma sp. GS8-3. In Fig. 3.3, we see the

major volatiles emitted from GS8-3; 2-methyl-1-propanol and 3-methyl-1-butanol failed to

reduce disease and pathogen population in Arabidopsis. On the contrary, methacrylic acid and

isobutyl acetate reduced disease severity and the pathogen population, leaving little doubt that

the age of the fungal culture is the likely reason behind the negative effects of VOC emitted by

63

Phoma sp.GS8-3 in Arabidopsis; however, we did not test this further. From our results, the

volatile compounds, methacrylic acid, isobutyl acetate, 3-octanone, m-cresol and phenyl ethyl

alcohol, were found to reduce disease severity, and are potential candidates for biological control

agents.

When we used these two major volatile organic components and well-characterized mutants and

transgenic plants to clarify the signaling pathways involved in this VOC-mediated ISR, our data

revealed that plant protection was completely arrested in mutant jar1 after treatment with MeBA,

a paradigm of JA-dependency. Although JA and ET are thought to be the signal transduction

molecules for induced systemic resistance (ISR) by biological control agents and JA and ET

share a common pathway in ISR (Pieterse et al. 1998), in our case, disease in an ethylene-

impaired mutant plants (ein3) was significantly suppressed, similar to the wild-type plants,

indicating that an independent JA-signalling pathway is involved in MeBA-accelareted ISR.

Disease severity in Arabidopsis transgenic NahG, defective in SA-dependent signaling, was

higher than in the control although the pathogen population was significantly reduced compared

with the control. But NPR1-activity-impaired mutant plants did not differ from wild-type plants

in being protected by the volatile-induced resistance. Previously, PGPF or PGPR (rhizobacteria)-

mediated ISR in Arabidopsis was reported to involve a novel signaling pathway based on JA/ET

signals and regulated by NPR1 (Hossain et al. 2007; Yoshioka et al. 2012; Pieterse et al. 1998).

But in our case, PGPF-regulated MeBA-triggered ISR signalling pathways appear to be

involved, mainly via JA as a signal molecule with the partial recruitment of SA, but the ISR

signaled via JA/ET differs by requiring NPR1.

Similar to MeBA, m-cresol also induced ISR without involving an ET-signal molecule but

involved a JA-signaling pathway. Our results showed that m-cresol used a complete SA-

64

dependent signalling pathway to trigger ISR that requires NPR1. The signal transduction

pathway through SA accumulation is found in the systemic acquired resistance (SAR) induced

by pathogen attack (Durrant and Dong, 2004), while it is thought that JA and ET are the signal-

transducing molecules for induced systemic resistance (ISR) by biocontrol agents (BCAs)

(Pieterse et al. 1998). However, there are some reports that SA can also work as an inducement

factor of ISR by BCAs (Hossain et al. 2007; Yoshioka et al. 2012). Our results also proved the

involvement of both SA- and JA-signal transduction in ISR.

For more confirmation of the molecular mechanisms behind the VOC-mediated ISR, we

assessed transcription levels of Arabidopsis defense-related markers, SA-, JA/ET-inducible

genes (Table 3.2) by real-time qRT-PCR analysis. Like the results of the mutant screening, m-

cresol significantly induced the SA-inducible marker genes PR1 and PR2, confirming that the

volatile lowered disease severity by inducing systemic resistance mainly through the SA-signal

transduction pathway. In addition, JA-inducible gene PDF1.2 was expressed significantly by

treating plants with m-cresol, strengthening our idea of a partial engagement of JA-regulation.

On the other hand, of all the genes examined, expression of the JA/ET-signal gene PDF1.2 was

the highest in MeBA-treated plants, more than 11-fold higher than in the control. Moreover, the

JA-inducible marker genes MYC2 and VSP2 were also amplified significantly by the MeBA

treatment. Thus, we are more confident that the JA-signaling pathway is activated in MeBA-

mediated ISR in Arabidopsis. MeBA also induced transcription of the SA-responsive PR1 gene,

supporting our mutant-screening data. Generally, regulation of PDF1.2 after pathogen infection

requires concomitant activation of JA- and ET-signaling pathways. However, our results provide

substantial evidence that the PGPF-emitted VOC m-cresol and MeBA induce PDF1.2 using the

JA-signal independently of ET-signaling. Although, we cannot explain the reason, the ET-

65

responsive gene PR4 was significantly expressed by m-cresol treatment compared with the

control, whereas ET-impaired mutants (ein2) showed no involvement of ethylene in the

resistance elicited by MeBA or m-cresol. However, studies on other volatile components from

different sources indicated various modes of action can be involved. For instance, Ryu et al.

(2004) revealed that the rhizobacterial volatile 2-3-butanediol and acetoin employed an ET-

signaling pathway independent of the SA- and JA-signals, completely opposite of the mechanism

induced by our volatiles. Lee et al. (2012) also found ISR by a long-chain volatile isolated from

Paenibacillus polymyxa E681 that primed expression of SA-, JA- and ET-signaling marker

genes. From another study, C6-aldehyde volatiles from green leaves of Arabidosis induced

resistance involving the JA-signaling pathway in Arabidopsis against a necrotrophic pathogen

(Kishimoto et al. 2006). However, the response of Arabidopsis to different volatile compounds

differed because the amount and type of the elicitors varied, depending on the source of the

volatiles; each of the multiple pathogen-associated molecular patterns (PAMPs) used by

microorganisms are recognized by different receptors, and they activate different pathways

(Hossain et al. 2007).

In conclusion, the present observations highlight the use of volatile organic components emitted

from beneficial fungi as a new strategy for biocontrol. Although a volatile compound is difficult

to apply in the field due to its evaporative nature and its efficacy is low compared with other

chemical pesticides, some volatile compounds have been used successfully in the field to control

plant disease (Song and Ryu, 2013). On the other hand, chemical inducers of resistance are

hampered by their own hazards including negative effects on plant growth (Heil et al. 2001).

MeBA and m-cresol have been used as antimicrobial compounds (Morris et al. 1979), and

according to the material safety data sheet of Science lab.com, both (especially m-cresol

66

according to Roberts et al. (1977) is corrosive to human skin and eyes at high concentrations. But

in our observation, m-cresol was nontoxic to Arabidopsis plants even at high concentration (100

mM). Considering that point, both of these volatiles were able to prime systemic resistance even

at very low concentrations, and perhaps only very low concentrations (1 μM) need to be applied

(Fig.3.4). However, further experiments in the greenhouse or open field using different crop

plants are needed before these compounds can be recommended for commercial use.

67

CHAPTER 4

Analysis of microarray data and prediction of transcriptional regulatory elements related with Disease resistance

68

Analysis of microarray data and prediction of transcriptional regulatory elements related with Disease resistance

4.1 INTRODUCTION

Plants utilize diverse and sophisticated signaling cascades for recognizing and responding to a

wide range of biotic and abiotic stresses. Stress recognition and signaling is translated into

biochemical reactions, metabolic adjustments and an altered physiological state. Thus, plants

have evolved defense mechanisms by which they can increase their tolerance against such

stresses. Consequently, a complex signaling network underlies plant adaptation to these adverse

environmental conditions (Zhu 2001). There has been rapid progress in our understanding of

these signaling pathways over recent years. From these studies, it has become apparent that these

pathways rely on endogenous regulators, such as salicylic acid (SA), ethylene (ET) and jasmonic

acid (JA), to induce defense reactions (Glazebrook 2001). In the past few decades, an increasing

amount of research was devoted to the study of Induced Systemic Resistance (ISR) mechanisms.

Salicylic acid (SA) is a key regulator of plant defenses, both in the enhancement of local defense

responses and the establishment of the broad-based systemic acquired resistance (Mauch-Mani

and Métraux, 1998). Its production at the site of infection has been linked with the induction of

defense-related gene expression, the enhanced generation of reactive oxygen species (ROS) and

programmed cell death (Mur et al., 1996; Shirasu et al., 1997). The role of reactive oxygen

species, especially H2O2, in plant response to stresses has been the focus of much attention.

Hydrogen peroxide has been postulated to play multiple functions in plant defense against

pathogens. H2O2 may possess direct microbicidal activity at the sites of pathogen invasion. It is

used for cell-wall reinforcing processes: lignification and oxidative cross-linking of

hydroxyproline-rich proteins and other cell-wall polymers. It was found to be necessary for

69

phytoalexin synthesis. H2O2 may trigger programmed plant cell death during the hypersensitive

response that restricts the spread of infection. H2O2 has been suggested to act as a signal in the

induction of systemic acquired resistance by inducing defense genes. Recently H2O2 has been

proposed to be involved in the signal transduction pathways leading to acclimation and protection

from abiotic stresses (Elżbieta and Henryk, 2000). The connection between H2O2 and SA in the

signaling networks has been extensively documented for a number of stress responses, including

to pathogen elicitors, insect feeding, wounding, high temperature and ABA associated stomatal

closure (Larkindale and Knight 2002; Apel and Hirt 2004; Peng et al. 2004; Mateo et al.).

Some non-pathogenic soil inhabiting saprophytes that significantly promote plant growth are

called plant growth promoting fungi (PGPF). Colonization of root with PGPF can also lead to

systemic resistance in distal parts of the plant (Meera et al. 1994, Meera et al. 1995). An

example of a PGPF is Penicillium simplicissimum GP17-2, which was found to control soil-borne

diseases effectively (Hyakumachi, 1994). Examination of local and systemic gene expression

revealed that culture filtrate of GP17-2 modulate the expression of genes involved in both the SA

and JA/ET signaling pathways. Phytohormones are acting on this signal transduction alone or

interact each other in a cooperative, competitive or interdependent way. This relationship

between phytohormones is a part of the transcriptional network for complex phytohormones

responses. These transcriptional networks are biologically important for plants to respond against

any kind of environmental stress. Promoter regions of stress-inducible genes contain cis-acting

elements involved in stress-responsive gene expression. Precise analysis of cis-acting elements

and their transcription factors can give us an accurate understanding of regulatory systems in

stress-responsive gene expression. The DNA microarray has recently emerged as a powerful tool

in molecular biology research, offering high throughput analysis of gene expression on a

70

genomic scale. Microarrays have already been used to characterize genes involved in the

regulation of circadian rhythms, plant defense mechanisms, oxidative stress responses, and

phytohormone signaling (Aharoni and Vorst, 2002). Microarray data can serve a long list of up-

regulated as well as genes with no response to stresses, and thus has a potential to identify

corresponding cis-regulatory elements. In Arabidopsis plant, thousands of genes have been found

as up-regulated and down-regulated from microarray analysis of the stress-inducible genes

(Kubota et al. unpublished). In order to identify cis-regulatory elements without using microarray

there are some other methods have also been established. A large number of Arabidopsis cis-

regulatory elements have been identified by a recently developed bioinformatics methodology

named LDSS (Local Distribution of Short Sequences) (Yamamoto et al., 2007). There are 308

octamers have successfully been detected that belong to a group of putative cis-regulatory

elements, Regulatory Element Group (REG), in addition to novel core promoter elements

(Yamamoto et al. 2009) by applying LDSS method in Arabidopsis genome. Biological role of

most of the REG is still not very clear. In order to give biological annotation to cis-regulatory

elements, one of the best methods is to analyze the microarray data and to predict cis-elements

from the genes response to environmental stress.

In my laboratory, microarray analysis to see transcriptional response of Arabidopsis treated with

GP17-2 in roots has been performed. Taking advantage of the in house data, I analyzed the

microarray data in detail, by comparing selected public microarray data of pathogen,

phytohormones, hydrogen peroxide (H2O2), and wound responses. Utilizing the microarray data,

I achieved in silico promoter analysis in order to reveal participating cis-regulatory elements

involved in the GP17-2-mediated ISR. An octamer-based frequency comparison method that has

71

been developed in our laboratory was used for the prediction. Special care was taken for cross-

detection by prediction of the SA/H2O2 response.

72

4.2 MATERIALS AND METHODS

4.2.1 Promoter analysis of genes related with Induced Systemic Resistance (ISR)

Microarray data of the PGPF Penicillium simplicissimum GP17-2 treatment (Kubota et al.

unpublished) were subjected to comparative analysis with microarray public data of different

phytohormones treatments. Raw data of 6 and 24 hrs post GP17-2 treatment and SA, JA, ET,

ABA and hydrogen peroxide treatment (obtained from the database TAIR,6,) were analyzed to

get fold change data of gene expression compared to control treatment using the software Excel

(Microsoft Japan, Tokyo).

4.2.2 Analysis of microarray data and Prediction of cis-regulatory elements:

4.2.2.1 Promoter sequence:

Promoter sequence from -1,000 to -1 relative to the major TSS (Transcription start site) was

prepared for 14,960 Arabidopsis genes. Major TSS was determined with large scale TSS tag

sequencing (Yamamoto et al., 2009) or 5’ end information of RAFL cDNA clones (Seki et al.,

2002; Yamamoto and Obokata, 2008). Identification of core promoter elements in a position-

sensitive manner was achieved as described previously (Yamamoto et al., 2009). Arabidopsis

genome and its gene models were obtained from TAIR (TAIR 6).

4.2.2.2 Preparation of RAR tables and promoter scanning:

Microarray data (Table 4.1) was used to prepare gene lists that show expression with more than 3

fold over the control. RAR (Relative Appearance Rate) for each octamer was calculated as the

following formula.

RAR= (count in an activated promoter set/number of promoters in the set)/ (count in total

promoters/ number of total promoters)

73

For each octamer-RAR combination, P value was calculated by Fisher’s Exact Test. P values

were once transformed into LOD scored, and RAR values with the LOD score less than 1.3 (P=

0.05) were filtered out to set as 0. The masked RAR are referred to as RARf in this report. RAR

and RARf values for REG annotation (Table 4.2) were calculated in a direction-insensitive

manner, where information of the complementary octamers was merged. Promoter scanning with

RAR, RARf and LOD tables were achieved using a home made Perl script and Excel (Microsoft

Japan, Tokyo). Promoters used for scanning showed over 5 fold-activation by hormones and

culture filtrate of PGPF treatment.

4.2.2.3 Scanning of promoter to select cis-regulatory elements:

To predict elements, all the promoters were scanned for the octamers of high RAR or RARf

value. For scanning of the promoters, a newly developed method by Yamamoto et al.

(unpublished) was followed. Phytohormone responsive promoters were scanned by analyzing the

RAR and RARf (Fig. 4.2). In some cases, multiple octamers with high RAR/RARf make a

cluster by overlap (Fig. 4.1). In that case, cis- elements were extracted as the overlapped region.

74

Example of promoter: ACGTCCCTTCAAACTAGCT

Octamer RAR value

ACGTCCCT 3.8

CGTCCCTT 5.3

GTCCCTTC 4.2

TCCCTTCA 1.2

Predicted sequence = ACGTCCCTTC

Fig. 4.1. RAR value of the octamers in a promoter. In this case, the selection was

ACGTCCCTTC

75

4.3 RESULTS

4.3.1 Comparative analysis of transcriptome related with Induced Systemic Resistance (ISR)

Microarray data of GP17-2 and phytohormone treatment were subjected to comparative analysis.

Results showed that there is a peak of SA/H2O2 response at 6 hours post GP17-2 treatment, and

another peak of abscisic acid (ABA) response at 24 hours post GP17-2 treatment (Fig. 4.2).

These results indicate that the GP17-2 treatment causes a sequence of responses from SA/H2O2

to ABA. Therefore, GP17-2 response is partially overlapped salicylic acid, hydrogen peroxide

and abscisic acid signaling during ISR caused by it.

4.3.2 Cis –element prediction for Phytohormones and CF of PGPF responses:

Prediction of cis-regulatory elements for PGPF and plant hormone responses were achieved

based on the microarray data shown in Table 4.1. Because ISR of Arabidopsis thaliana by a

PGPF, Penicillium simplicissimum GP17-2, is known to be activated by the treatment of roots by

culture filtrate (CF) of culture medium of PGPF, this experimental scheme was selected as a

model of ISR by PGPF. CF response was monitored at aerial parts excluding roots with

application of CF in the presence or absence of pathogen (Pseudomonas syringae pv tomato

DC3000) infection (Table 4.1). Microarray data was used to identify up-regulated genes by the

stimuli, and the corresponding promoter sequences were subjected to statistical analysis to

calculate.

4.3.2 Selection of Phytohormone Salicylic acid (SA) responsive cis-element from over-

represented genes:

Salicylic acid responsive cis-elements were selected from the microarray data of Goda et al

(2008).Total 197 up-regulated genes were analyzed for SA responsive cis-element selection.

76

Total six octamers have found with high RAR value against SA response. Among them, SA-1,

SA-2 and SA-3 have been selected depending on the level of expression (RAR value >3.0)

against Salicylic acid treatment. On the other hand, SA+CF-1, SA+CF-2 and SA+CF-3 were

selected upon the expression level of the octamer to SA and culture filtrate of the PGPF (GP17-

2) treatment. SA-1, SA-2 and SA+CF-2 were selected from the same promoter that has been

reported as P-loop containing nucleoside triphosphate hydrolases superfamily protein; functions

in nucleoside-triphosphatase activity, ATPase activity, nucleotide binding and ATP binding. In

the same way, SA+CF-1 and SA+CF-3 were selected from same the promoter, that is a member

of WRKY Transcription Factor; Group III, having sequence-specific DNA binding

transcription factor activity and biologically involved in defense response to bacterium,

regulation of transcription, DNA-dependent, salicylic acid mediated signaling pathway. SA-3

was selected from the promoter encodes a UDP-glucosyltransferase, UGT74E2, which acts on

IBA (indole-3-butyric acid) and affects auxin homeostasis. The transcript and protein levels of

this enzyme are strongly induced by H2O2 and may allow integration of ROS (reactive oxygen

species) and auxin signaling (http://arabidopsis.org/servlets/TairObject?id=39846&type=locus).

No REG was found among the selections. But, the octamer of SA-1 has 5 bases overlapping

with one of the REG elements. Octamer of SA+CF-3 was also found having 7 bases overlapped

with another REG element. RAR (RARf) value of the octamer of SA-1, SA-2, SA-3 was 4.36,

4.23 and 5.12 respectively against SA treatment where as octamers of SA+CF-1, SA+CF-2 and

SA+CF-3 having RAR value of 3.5, 4.4 and 6.1 respectively for SA response and 3.3, 3.2 and

3.5 respectively for CF response (Table 4.2, Fig. 4.3).

4.3.3 Selection of CF responsive cis-element from over-represented genes:

77

Following the same scanning procedure, cis-regulatory elements were extracted for CF (CF-P)

responsive and CF with Pathogen (CF+P) responsive elements from over expressed genes. Total

four cis-elements were selected. Among them, CF+P1, A CGCG box containing sequence was

found in the CF followed by Pathogen infection treatment responsive promoter known as

biologically involved in carbohydrate biosynthetic process, response to water deprivation and

having transferase activity, transferring glycosyl and hexosyl groups. CGCG box is well known

as a member of the Calmodulin-binding protein family which is involved in multiple signaling

pathways in plants (Yang and Poovaiah, 2002). CF+P2 was extracted from the promoter encodes

protein phosphatase 2C (PP2C) and also reported as negative regulator of ABA signaling.

Abscisic acid interacts antagonistically with salicylic acid signaling pathway (Chang-Jie Jiang et.

al. 2010). This gene has also been reported responsive to abscisic acid stimulus, cold and water

deprivation. The mRNA up-regulated by drought and ABA. The octamer of CF+P2 have 5 bases

overlapped with a REG element. In case of CF (no pathogen) responsive element CF-P1, a REG

element containing T/G box- AACGTG was extracted which is reported for MYC protein

binding TF. Boter at el. (2004) revealed that JAMYC/AtMYC2 transcription factors recognizing

a T/G-box AACGTG motif in this promoter fragment play key role in JA-induced defense gene

activation. This REG element is positioned at -183 bp from TSS in the promoter that encodes the

large subunit of ADP-glucose pyrophosphorylase, the enzyme which catalyzes the first and

limiting step in starch biosynthesis. CF-P2 was extracted from the promoter which Encodes a

chloroplast/cytosol localized serine O-acetyltransferase involved in sulfur assimilation and

cysteine biosynthesis having cellular response to sulfate starvation and cold. RAR (or RARf)

value of the octamers of CF+P1, CF+P2, CF-P1 and CF-P2 was 7.5, 10.33, 3.05 and 18.11

respectively against CF (+/-) pathogen treatment (Table 4.2).

78

4.3.4 Selection of H2O2 responsive cis-element from over-represented genes:

For H2O2 responsive genes, total 6 cis-regulatory elements were selected. H2O2-1 was extracted

from the promoter which encodes a UDP-glucosyltransferase, UGT74E2, which acts on IBA

(indole-3-butyric acid) and affects auxin homeostasis. The transcript and protein levels of this

enzyme are strongly induced by H2O2 and may allow integration of ROS (reactive oxygen

species) and auxin signaling. H2O2-2 was selected from the gene involved in carbohydrate

metabolic process having endo-1, 4-beta-xylanase activity, hydrolase activity and hydrolyzing O-

glycosyl compounds. H2O2-3 is extracted from the gene is noticed for cell differentiation, cell

proliferation and organ morphogenesis. That octamer has 7 bases overlapped with one REG

element. H2O2+ CF-1 was extracted from the promoter involved in response to Heat, high light

intensity and hydrogen peroxide. H2O2+CF-2 was selected form the gene which has alcohol

dehydrogenase (NAD) activity and catalyzes the reduction of acetaldehyde using NADH as

reductant, biologically involved in cellular respiration, and response to cadmium ion, hypoxia,

osmotic stress and salt stress. H2O2+CF-3 was extracted from the gene involved in toxin

catabolic process and has glutathione transferase activity at molecular level. No REG element

was matched with the H2O2 responsive cis-regulatory element selections. RAR (RARf) value of

the octamer of H2O2-1, H2O2-2, H2O2-3 was 9.3, 8.6 and 10.46 respectively against H2O2

treatment where as octamers of H2O2+CF-1, H2O2+CF-2 and H2O2+CF-3 having RAR value of

6.9, 5.7 and 8.2 respectively for H2O2 response and 3.3, 5.1 and 4.4 respectively for CF response

(Table. 4.2).

Cross-detection of the same elements by SA, H2O2, or CF suggests their possible crosstalk

(Table 4.2) in the transcriptional network of ISR (Fig: 4.5). For instance, the octamer of H2O2-1,

H2O2-2 and H2O2+CF-1 showed over-expression (high RAR value) against SA treatment. Likely,

79

CF-P2 also showed high expression value in case of H2O2 treatment (Table 4.2). This result

indicates multiple cross-talking of the cis-regulatory elements in the transcriptional network of

ISR by PGPF (Fig. 4.5).

4.3.5 Construction of synthetic promoter by the predicted cis-elements:

Synthetic promoters contain three copies of each element with spacer sequence (AAAA) (Fig.

4.4). Restriction enzyme sites were included at right and left end respectively.

80

B

Fig. 4.2 Comparative analysis of microarray data of PGPF and phytohormone treatment.

A. Hierarchical luster comparing gene expression profiles of Arabidopsis plants treated by

cell-free culture filtrate of P. Simplicissimum GP-17-2 (PGPF) with various

phytohormone treatments. B. Time-course expression pattern of GP17-2 responsive genes with more than 3 fold

induction by SA, H2O2 and ABA

81

Fig. 4.3. Showing the fold of expression level of the octamers of SA and CF + Pathogen

responsive promoter (-400--10). Line graph showing RAR and bar graph showing RARf value of

the octamers.

0

1

2

3

4

5

6

0

1

2

3

4

5

6

-400

-385

-370

-355

-340

-325

-310

-295

-280

-265

-250

-235

-220

-205

-190

-175

-160

-145

-130

-115

-100 -8

5-7

0-5

5-4

0-2

5-1

0

SA-RARf

SA-RAR

SA-CF-SA--2

SA-CF-2SA--2 SA-1

0

0.5

1

1.5

2

2.5

3

3.5

-400

-385

-370

-355

-340

-325

-310

-295

-280

-265

-250

-235

-220

-205

-190

-175

-160

-145

-130

-115

-100 -8

5-7

0-5

5-4

0-2

5-1

0CF+patho -RARfCF+patho -RAR

SA-CF-2

82

SA-1: CAAAA SA-1 AAAA SA-1 AAAA SA-1 AAAAG SA-2: CAAAA SA-2 AAAA SA-2 AAAA SA-2 AAAAG SA-3: CAAAA SA-3 AAAA SA-3 AAAA SA-3 AAAAG SA+CF-1: CAAAA SA+CF-1 AAAA SA+CF-1 AAAA SA+CF-1 AAAAG SA+CF-2: CAAAA SA+CF-2 AAAA SA+CF-2 AAAA SA+CF-2 AAAAG SA+CF-3: CAAAA SA+CF-3 AAAA SA+CF-3 AAAA SA+CF-3 AAAAG CF+P-1: CAAAA CF+P-1 AAAA CF+P-1 AAAA CF+P-1 AAAAG CF+P2 : AGCTTAAAA CF+P2 AAAA CF+P2AAAA CF+P2 AAAAG CF-P1: AGCTTAAAA CF-P1 AAAA CF-P1 AAAA CF-P1 AAAAG CF-P-2: AGCTTAAAA CF-P-2 AAAA CF-P-2 AAAA CF-P-2 AAAAG H2O2-1: CAAAA H2O2-1 AAAA H2O2-1 AAAA H2O2-1 AAAAG H2O2-2: CAAAA H2O2-2 AAAA H2O2-2 AAAA H2O2-2 AAAAG H2O2-3: CAAAA H2O2-3 AAAA H2O2-3 AAAA H2O2-3 AAAAG H2O2+CF-1: CAAAA H2O2+CF-1 AAAA H2O2+CF-1 AAAA H2O2+CF-1 AAAAG H2O2+CF-2: CAAAA H2O2+CF-2 AAAA H2O2+CF-2 AAAA H2O2+CF-2 AAAAG H2O2+CF-3: AGCTTAAAA H2O2+CF-3 AAAA H2O2+CF-3 AAAA H2O2+CF-3 AAAAG

Fig. 4.4: Structures of synthetic promoter. Each of the elements was inserted with three times replication

along with four spacer AAAA.

83

Fig. 4.5 Possible cross- talk between PGPF and phytohormone signaling pathways

84

Table 1. Extraction of overrepresented octamers in promoters with hormone and CF

response.

Microarray Ref Number of up-regulated genes

CF response (6 h) Kubota et al. unpublished 127

CF response (24 h) Kubota et al. unpublished 361

CF response during pathogen infection (Pseudomonas syringae pv tomato DC3000, 24 h)

Kubota et al. unpublished 362

Pathogen infection (Pseudomonas syringae pv tomato DC3000, 24 h)

Kubota et al. unpublished 965

SA Goda et al, 2008 (TAIR_ME00364) 197

H2O2 Yamamoto et al, 2004 260

85

Table 2: RAR (RARf) value of the selected octamers in response to different treatments

Element Length of CF 6h CF 24h CF+P 24h Path 24h H2O2 SA element (bp)

SA-1 12 0 0 0 0 0 4.36

SA-2 12 0 0 1.97 0 0 4.23

SA-3 12 0 0 0 0 0 5.12

SA+CF-1 14 0 3.34 0 1.63 0 3.52

SA+CF-2 12 0 3.2 0 0 0 4.4

SA+CF-3 14 0 3.5 0 0 0 6.15

H2O2-1 8 0 0 0 0 9.329 6.16

H2O2-2 11 0 0 0 0 8.629 3.8

H2O2-3 9 0 0 0 0 10.46 0

H2O2+CF-1 8 0 3.31 0 0 6.9 3.03

H2O2+CF-2 8 0 5.17 0 0 5.75 1.89

H2O2+CF-3 12 0 4.43 0 0 8.218 2.71

CF+P-1 15 0 0 7.5 0 0 0

CF+P-2 12 0 0 10.33 0 0 0

CF-P-1 14 0 3.05 2.28 2.47 0 0

CF-P-2 12 18.119 0 0 0 8.85 0

86

4.4 DISCUSSION Plant development and environmental adaptation is organized by phytohormones through cell-to

cell signal transduction. Multiple cross talking of different phytohormone activities are involved

in the transcriptional regulation of this signal transduction. Phytohormones are acting on this

signal transduction alone or interact each other in a cooperative, competitive or interdependent

way. This relationship between phytohormones is a part of the transcriptional network for

complex phytohormones responses. These transcriptional networks are biologically important for

plants to respond against any kind of environmental stress.

Previous researches showed that some phytohormones are involved in activation of systemic

immunity by pathogen infection. Specially, the salicylic acid content and expression of salicylic

acid, jasmonic acid and ethylene inducible genes has increased significantly in the plants

inoculated with PGPF and become resistant to pathogen infection. This suggests the involvement

of several phytohormones in systemic resistance induced by PGPF.

There has been rapid progress in our understanding of these signaling pathways over recent

years. In the past few decades, an increasing amount of research was devoted to the study of ISR

mechanisms. Salicylic acid (SA) is a key regulator of plant defenses, both in the enhancement of

local defense responses and the establishment of the broad-based systemic acquired resistance

(Mauch-Mani and Métraux, 1998). Its production at the site of infection has been linked with the

induction of defense-related gene expression, the enhanced generation of reactive oxygen species

(ROS) and programmed cell death (Mur et al., 1996; Shirasu et al., 1997). The role of reactive

oxygen species, especially H2O2, in plant response to stresses has been the focus of much

attention. Hydrogen peroxide has been postulated to play multiple functions in plant defense

against pathogens. H2O2 may trigger programmed plant cell death during the hypersensitive

87

response that restricts the spread of infection. H2O2 has been suggested to act as a signal in the

induction of systemic acquired resistance by inducing defense genes. The connection between

H2O2 and SA in the signaling networks has been extensively documented for a number of stress

responses, including to pathogen elicitors, insect feeding, wounding, high temperature and ABA

associated stomatal closure (Larkindale and Knight 2002; Apel and Hirt 2004; Peng et al. 2004;

Mateo et al. 2006). Considering the above mentioned circumstances, my present study was aimed

to identify the phytohormones and/or PGPF responsive element in the promoter of stress

inducible genes. My long term goal was to understand characteristics of promoter that support the

huge transcriptional network where multiple hormones are supposed to be committed to the

PGPF induction of disease resistance.

Promoter sites that are over-representing in the microarray-positive promoters over total

promoters in the genome were detected as putative cis-elements. Further analyses of these

candidates revealed that some elements correspond to another type of putative cis-regulatory

elements, REG, which is suggested to function in a position-sensitive fashion. The other

predicted elements are thus suggested to be of a position-insensitive type (s). Total 16 synthetic

promoters have been constructed in this experiment. Cross-detection of the same elements by

SA, H2O2, or CF suggests their possible crosstalk. Elzbieta et al. (2000) reported that,

pathogenic infection enhances ROS-dependent signaling system to induce H2O2 and SA that

activate transcription factors for the expression of defense genes in SAR pathways. On the other

hand, PGPF induces ROS-dependent signaling system to activate SA and H2O2 that stimulate

transcription factors for the defense gene expression in ISR pathway (David et al., 2008). This

suggests that PGPF induced systemic resistance (ISR) might share SAR signaling pathway

88

involving SA and H2O2 responsive cis-regulatory elements in the transcriptional network of

disease resistance.

Transcriptional profiling is particularly informative to understand transcriptional responses. In

my laboratory, microarray analysis to see transcriptional response of Arabidopsis treated with

GP17-2 in roots has been performed. Taking advantage of the in house data, I analyzed the

microarray data in detail, by comparing selected public microarray data of pathogen,

phytohormones, hydrogen peroxide (H2O2), and wound responses. Results showed that there is a

peak of SA/H2O2 response at 6 hours post GP17-2 treatment, and another peak of abscisic acid

(ABA) response at 24 hours post GP17-2 treatment. These results indicate that the GP17-2

treatment causes a sequence of responses from SA/H2O2 to ABA.

Utilizing the microarray data, I achieved in silico promoter analysis in order to reveal

participating cis-regulatory elements involved in the GP17-2-mediated ISR. An octamer-based

frequency comparison method that has been developed in our laboratory was used for the

prediction. Special care was taken for cross-detection by prediction of the SA/H2O2 response.

This study was composed of two parts: prediction of putative transcriptional regulatory elements

by analyzing Arabidopsis microarray data with the help of bioinformatics study, and

preparation of synthetic plant promoters by using the predicted putative cis-regulatory elements

to diagnose the regulatory responses of the elements in transcriptional network. Promoters

responsive to SA, H2O2 and culture filtrate (CF) of PGPF, identified by the corresponding

microarray data, were subjected to the prediction.

89

CHAPTER 5

Construction of luciferase based vectors using synthetic promoters and their functional

analysis in planta

90

Construction of luciferase based vectors using synthetic promoters and their functional analysis in planta

5.1 INTRODUCTION

Environmental stresses such as water deficit, high salinity, and low temperature adversely affect

the productivity and quality of agriculturally important crops (Bartels and Sunkar , 2005).

Genetic transformation has been become a powerful tool for the improvement of stress tolerance

of plants, and many stress-tolerant plants have been produced (Jaglo-Ottosen et al. 1998; Apse et

al. 1999; Yusuke et al. 2000; Hsieh et al. 2002; Kasuga et al. 2004; Zhang et al. 2004; He et al.

2005; Zhang et al. 2011).

Some promoters are known to be activated by osmotic stress, high salt, drought, or ABA

treatment (Yamaguchi-Shinozaki and Shinozaki 1994; Wang et al. 1995). Moreover, different

cis-acting elements in these promoters are involved in stress-responsive gene expression

(Yamaguchi-Shinozaki and Shinozaki 2005). ABRE (ABA-responsive element) and DRE/CRT

(dehydration-responsive element/C repeat) are major cis-acting elements in abiotic stress-

inducible gene expression. DRE/CRT elements with the core sequence C/DRE (GCCGAC) play

an important role in regulating gene expression in ABA-independent regulatory systems and can

be found in promoter regions of many dehydration-, high-salt-, and cold-stress inducible genes in

Arabidopsis, such as rd29A, kin1, and cor15a (Baker et al. 1994; Wang et al. 1995; Kim et al.

2002). Various types of ABRE-like sequences have been reported, including the G-box sequence

(CACGTG), which is present in a large number of environmentally regulated genes (Menkens et

al. 1995). Other cis-regulatory elements, such as MYB (C/TAACNA/G), MYC (CANNTG),

LTRE (CCGAC) play key roles in activating gene expression in response to osmotic stress

91

and/or ABA (Baker et al. 1994; de Bruxelles et al. 1996; Abe et al. 2003; Nakashima et al.

1997).

Applications in plant genetic engineering with transcription factors driven by stress-induced

promoters provide an opportunity to improve the stress tolerance of crops (Viswanathan and Zhu

2002). However, the activities of native promoters identified so far have certain limitations, such

as low expression activity and low specificity. A series of synthetic promoters for higher-level

expression of foreign genes has been reported in the literature (Mitsuhara et al. 1996; Rushton et

al. 2002; Shin et al. 2003; Kobayashi et al. 2004; Bhullar et al. 2011). With the information

currently available on the regulatory mechanisms of abiotic stress tolerance in plants, it is now

feasible to construct strong inducible promoters artificially. Thus, in the current study, I have

selected cis-regualtory elements derived from stress-induced promoters (e.g. PGPF,

phytohormone) in Arabidopsis, to construct artificial promoters. The pattern of inducibility

driven by these artificial synthetic promoters was characterized in stable transgenic Arabidopsis

by monitoring expression of the luciferase (LUC) reporter gene, upon exposure of these plants to

various stress conditions. In addition, promoter activity was assessed through luminescence

estimation of LUC expression in transgenic plants under various stress conditions (biotic and

phytohormone) as compared to the wild type Col-0 and /or vector control.

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5.2 MATERIALS AND METHODS

5.2.1 Construction of LUC vector

LUC+/tNOS from yy327(Yamamoto et al. 2003) and pNOS::BAR/tOCS from SL J75515

(http://www.tsl.ac.uk/research/jonathan-jones/plasmids.htm) were inserted into the

BamHI/HindIII and EcoRI sites of a binary vector, pPZP200, respectively (Hajdukiewicz et al.,

1994) to make yy326. A modified CIP7 intron with a 12-bp deletion was prepared as a cassette for

copy number estimation by competitive PCR (Yamamoto et al., 2003), and inserted into the SacI

site of yy326. Subsequently, -46 to +8 region of the 35S promoter of Cauliflower Mosaic Virus

(CaMV 35S) (Benfey and Chua, 1990), containing a TATA box, was inserted into the BamHI site.

Map of the final construct, yy447, is shown in Fig. 5.1.

5.2.2 Construction of synthetic promoters

A synthetic promoter construct (CF+P-1) was produced by annealing sense and antisense

oligonucleotides of a circadian controlled regulatory element (data not shown), and inserted into

the SacI/BamHI site of yy447 to make yy462. Prepared vectors, including yy462 were used for

transformation of Arabidopsis via Agrobacterium tumefaciens GV3101 pMP90 (Koncz and

Schell, 1986)

5.2.3 Plant transformation

Arabidopsis thaliana Col were transformed by the floral dipping method (Clough and Bent,

1998). Dipped plants were places in a plastic tray and covered with a tall clear-Plastic dome to

maintained humidity. Plants were transferred in a low light or dark location overnight and

returned to the growth chamber on the next day; care was taken to keep domed plants out of

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direct sunlight. Plastic domes were removed approximately 12-24 h after transformation and

plants were grown for a further 3-5 weeks until siliques turn to brown color and dry.

5.2.4 T1 selection and copy number estimation of T-DNA

T1 transgenic seeds were sown on GM –agar plates (Valvekens et al., 1988) supplemented with

cefotaxime at 100 mg/L and BASTA (gluphosinate ammonium, Crescent Chemical, Co.,

Hauppauge, NY) at 10mg/L. BASTA tolerant green plants with a long primary root were

transferred to soil after 7-10 days (Fig. 5.2).

BASTA-resistant T1 plants were subjected to estimation of copy number of T-DNA by PCR.

Preparation of PCR template from plant tissue was essentially followed by the alkali-boiling

method (Klimyuk et al., 1993). A leaf from a T1 plant was put into a well of 96-hole PCR plates.

After addition of alkaline solution (40μl of 0.25M NaOH), samples were incubated at 95 0C for

5 min. Then 40μl of 0.25M of HCl were added to the leaf sample together with 20 μl of

0.5M Tris-HCl (0.25% NP-40) and incubated for more 2 min at 95 0C. 1 μl of that T-DNA

sample was used for PCR to estimate the copy number.

Primers used for the PCR were CIP7SF (5’-TCT GTT CAC TCT CTT AGA TGC CAA A-3’)

and CIP7SR (5’-CAC AGA GTC CAC AAC AAT TGA AA-3’) (Fig. 5.3). Cycle conditions of

the competitive PCR was (94 0C for 1 min, 80 0C for 4 min) x 1 cycle, (94 0C for 15 sec, 50 0C

for 15 sec, 72 0C for 30 sec) x 40 cycles, and (72 0C for 5 min) x 1 cycle. The PCR products were

diluted with equal volume of TE buffer (10 mM Tris-Cl, 1 mM EDTA, pH 8.0), mixed with ¼

volumes of the loading dye solution containing 1 μg /ml VistraGreen (GE Healthcare Japan,

Hachioji), and separated by electrophoresis in 15% polyacrylamide gel with the electrophoresis

buffer (modified TBE: 50 mM Tris-Cl, 50 mM Borate, 1 mM EDTA). After electrophoresis, gels

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were scanned with a confocal laser scanner (Typhoon 9400, GE healthcare Japan, Hachioji).

Signal strength of each band was expressed numerically with ImageQuant 5.2 (GE healthcare

Japan, Hachioji) and calculated relative intensity of each pair of bands. The in vitro mix

experiments were performed with a DNA template of total Arabidopsis DNA and Plasmid DNA

(yy447) in different proportions, both of which had been digested with EcoRI to equalize their

template activity. Arabidopsis genomic DNA was isolated from Col-0 plants following CTAB

method (Murray and Thompson, 1980).

5.2.5 Selection of transgenic lines:

T1 transformants with single copy T-DNA were let to self and the resultant T2 seeds were

subjected to segregation analysis of the herbicide resistance. Single copy insertion at the T1

generation was confirmed by the comparative PCR analysis at the T2 generation.

5.2.5 in vivo luciferase assay

Seeds of transgenic lines containing synthetic promoter and vector control were sown on GM

plates supplemented with 0.8% Bactoagar (Japan BD, Tokyo) and 1% sucrose. Plates were kept

in the dark for 2-4 days at 4 oC for vernalization and then grown in a growth chamber at 22 oC

under 18L/ 6D cycle at the light intensity of 6-8 W m-2 for 14 days. Plants were sprayed with 1

mM luciferin solution 1 day prior to the assay (Kimura et al., 2001).

To analyze the effects of circadian rhythm on the expression of the synthetic promoter,

automated monitoring of bioluminescence was performed by using an automated 2-channel

photomultiplier system (Ishiura et al., 1998) inside the growth cabinet with the same growing

condition. During analysis, photons were counted under 18 h day/ 6 h night cycle for the first 2

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days followed by continuous low light for the next 3 days. The data from assay were logged into

a text file and subsequently analyzed using Excel software (Microsoft Japan, Tokyo, Japan).

5.2.6 in vivo luciferase assay of synthetic promoter in response to pathogen infection

Synthetic promoter (CF+P-1) inserted in to yy447 was brought to in vivo analysis to analyze its

response against the bacterial leaf speck pathogen P. syringae pv. tomato (Pst) DC3000

infection. About 60 seeds of 3 transgenic lines (T2) containing synthetic promoter were sown

on GM plates supplemented with 0.8% Bactoagar (Japan BD, Tokyo) and 1% sucrose. Plates

were kept in the dark for 2-4 days at 4 oC for vernalization and then grown in a growth chamber

at 22 oC under continuous low light (6-8 W m-2 ) for 10 days. Plants were sprayed with 1 mM

luciferin solution 1 day prior to the assay. Pst DC3000 inoculum was prepared following the

method as mentioned on chapter 2. About 1.5 ml of inoculum was sprayed to each plate. Control

was maintained by spraying with same amount of MgSO4 (10mM) solution. Then the plants

were placed in the photomultiplier to measure luciferase luminescence. Col-0 and yy447 plants

were used as control line.

5.2.7 in vivo luciferase assay of synthetic promoter in response to Abscisic acid

Synthetic promoter (CF+P-1) inserted in to yy447 was brought to in vivo analysis to analyze its

response to Abscisic acid. Seeds of T2 lines containing synthetic promoter were sown on GM

plates supplemented with 0.8% Bactoagar (Japan BD, Tokyo) and 1% sucrose. Plates were kept

in the dark for 2-4 days at 4 oC for vernalization and then grown in a growth chamber at 22 oC

under continuous low light (6-8 W m-2) for 2 weeks. Plants were then transferred to a 24 wel

plate (1 seedling/wel) filled with 500 μl of GM broth in each and grown for more 1 week. 1 mM

of luciferin solution was added to each wel 1 day prior to the assay. 100 μM ABA was added in

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each wel. Control was maintained by adding with 0.1% methanol (Me-OH) solution. Then the

plants were placed in the photomultiplier to measure luciferase luminescence.

5.2.8 in vivo luciferase assay of synthetic promoter in response to SA acid

Followed by the ABA treatment analysis, synthetic promoter (CF+P-1) was then brought to

analyze its response to SA acid treatment. The similar method was followed to grow plants as in

case of ABA treatment. Then 500 μM SA was added in each wel. Control was maintained by

adding with 0.1% Et-OH solution. Then the plants were placed in the photomultiplier to

measure luciferase luminescence.

5.2.9 in vivo luciferase assay of synthetic promoter in response to H2O2

Followed by the SA and ABA treatment analysis, synthetic promoter (CF+P-1) was then brought

to analyze its response to H2O2 treatment. The similar method was followed to grow plants as in

case of other hormone treatment. Then 3 % H2O2was added in each wel. Control was maintained

by adding with same volume of SDW. Then the plants were placed in the photomultiplier to

measure luciferase luminescence.

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Fig 5.1. Construction of synthetic promoters

(A) Illastration of LUC vector yy447. Elements were inserted between the SacI and BamHI sites upstream of the minimal region of 35S promoter of Cauliflower mosaic virus (CaMV_35S). LB: Left border, RB: Right border, BAR: BASTA (Phosphinothricin) resistance gene, selection marker for plants, CIP7 intron_ Δ 12: COP1-interacting protien 7( CIP7) intron with a 12-bp deletion, CaMV-35S minimal: -46 to +8 region of Cauliflower mosaic virus (CaMV_35S), LUC+ : firefly luminescent reporter, pNOS: nopaline synthase gene promoter, tOCS: octopine synthase gene terminator, tNOS: nopaline synthase terminator.

(B) Nucleotide sequence of the vector (yy447)

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Fig. 5.2. Selection of BASTA resistant plants on selective media. A. The whole plate showing

BASTA positive and negative plants. B. Part of plate with clear view of the BASTA resistant

Arabidopsis plants. White arrows indicate BASTA positive more healthy and green plants.

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Fig. 5. 3 : Estimation of T-DNA copy number by competitive PCR

A. Arabidopsis thaliana CIP7 intron

B. CIP7 Select-F and CIP7 Select-R are PCR primers used for the competitive PCR anneal

with CIP7 intron.

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5.3 RESULTS

5.3.1 Construction of synthetic promoter containing vector yy447:

Luciferase reporter based vector yy447 was constructed using yy326 as the core vector in

pPZP200. Figure 5.1A showing the map of the vector. A minimal promoter (-46 to +8 region of

CaMV-35S) containing TATA box was inserted as transcriptional enhancer. For the selection of

Arabidopsis transformants, a herbicide BASTA resistance gene BAR was introduced also. A

cassette for copy number estimation (12 bp deleted CIP7 intron) was inserted to screen the single

copy inserted transgenic plant. The firefly luciferase reporter genes LUC was introduced to

evaluate the gene expression. Finally, a circadian controlled cis-regulatory containing synthetic

promoter (data not shown) was inserted between BamHI and SacI restriction site. Prepared

vector was sequenced before transformation to Agrobacterium tumefaciens and nucleotide

sequences of all the inserts were carefully checked (Fig. 5.1B).

5.3.2 Estimation of the copy number of T-DNA

To estimate the T-DNA copy number inserted, in vitro DNA mix experiments were performed

with a DNA template of total Arabidopsis genomic DNA and Plasmid DNA (yy447) mixed in

different proportions: 1:0, 0:1, 1:1, and 2:1. For this analysis, competitive PCR was done using

a CIP7 intron with 12 base-deletion marker . T-DNA contains CIP7 intron which is 12 bp shorter

than Arabidopsis thaliana genomic CIP7and thus PCR product for T-DNA is 12-bp shorter than

that one for genomic DNA (Fig. 5.3 A&B ). Therefore, the lower band was indicating the T-

DNA amplification where as the upper band indicating the genomic DNA. Figure 5.3 (C&D)

showing the results of in vitro DNA mix experiments. When input (T-DNA/genome) was 1/2,

that means single copy of T-DNA was mixed with double copy of genomic DNA, the upper band

showed more intensity than the lower one (Fig. 5.3 C). Similarly, when input (T-DNA/genome)

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was 1/1, both the bands showed similar intensity. On the other hand, if the band intensity of T-

DNA is thicker than genomic DNA, it means, the plant inserted with multi copy (2 or 3 copies)

of T-DNA. The band intensity was calculated by using Image Quant 5.2 and numerical data of

the entire input ratio is shown in Fig. 5.3 D. Results showing that the relative intensity was

equally proportionate to the T-DNA/genome mixture ratio.

5.3.3 Selection of transgenic lines

T0 transformants were let to be selfed and T1 transformants were screened with BASTA

(herbicide) and greens seedlings with long root systems were separated to soil medium and

leaves were sampled for T-DNA preparation. To identify the single copy inserted plants,

competitive PCR was done using CIP7 intron with 12 bp deletion markers. Transgenic plants

with single copy insertion were identified on the basis of the results of the in vitro mix

experiments (Fig. 5.3C). Band intensity was compared between T-DNA and genomic DNA and

the bands similar to input mix T-DNA/genome: 1/2 were counted as single copy inserted plant

(Fig. 5.3). T1 transformants with single copy T-DNA insertion were let to be self-pollinated and

T2 seedlings were brought to perform PCR again with same primers of CIP7 intron to get

homozygous transgenic lines. Figure 5.4 is showing the gel picture of the segregation of single

copy T-DNA in T2 generation giving a 1:2:1 ratio. Positive homozygous lines were identified

by observing the bands with similar intensity while negative homozygous (not inserted with T-

DNA) was the line showing only one upper band (Fig 5.4). Heterozygous lines were counted as

the upper band is thicker than the lower. T3 seeds from the homozygous lines were used for

further assay. Total 48 seeds were sown for this screening, where the segregation pattern more or

less followed 1:2:1 ratio.

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5.3.4 Analysis of the activity of synthetic promoter:

Synthetic promoter inserted in the yy447 was brought to in vivo analysis to analyze its activity by

biological experiments. Since a circadian regulated synthetic promoter was introduced in to the

vector, we conducted a representative experiment controlling the seedling growth under LD 18:6

photoperiods followed by a continuous low light (LL) (6-8 W m-2) to observe the effect of

circadian clock on reporter gene expression. Fig. 5.5 showing the LUC gene expression

controlled by circadian clock comparing with the wild type (Col-0) Arabidopsis plant and the

vector control yy447 seedlings. Reporter gene expression was analyzed by observing the

luciferase luminescence that was expressed as countable photons after treatment with luciferin. A

diurnal rhythm was found in the transgenic plants under LD 18:6 photoperiods, while a circadian

oscillation of the reporter gene was observed under continuous low light (Fig. 5.5) with the peak

levels occurring around 6-7 hrs after subjective dawn.

5.3.5 in vivo analysis of synthetic promoters in response to pathogen infection

Synthetic promoter (CF+P-1) inserted in yy447 was brought to in vivo analysis to analyze its

response to pathogen infection. Bacterial leaf speck pathogen P. syringae pv. tomato (Pst)

DC3000 was used in this experiment as pathogen inoculum. Single copy synthetic promoter

containing T2 transgenic lines (3 lines) were subjected for this analysis. Data showed that all the

3 lines showed a repression of gene expression after few hours of pathogen treatment (Fig. 5.6).

Pathogen treatment was also found to disturb the circadian rhythm that showed by the control

plants.

5.3.6 in vivo analysis of synthetic promoters in response to phytohormone treatment

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Synthetic vector containing the element CF+P-1 was subjected to in vivo analysis to observe

reporter gene expression in response to phytohormone ABA and SA treatment. Fig. 5.7 and 5.8

showing that reported gene expression was repressed after treating with ABA and SA in CF+P-1

element containing transgenic plants. Circadian rhythm of the transgenic plants was also

disturbed after phytohormone treatment. In both cases, a slight up-regulation was found

immediately after treatment compared to mock followed by sharp repression. In case of SA

treatment, reporter gene expression was slightly recovered after about 30 hrs of treatment. But in

case of ABA treatment, no such pattern was found.

5.3.7 in vivo analysis of synthetic promoters in response to H2O2

Transgenic plants containing synthetic promoter of the element CF+P-1 were treated with H2O2

and reporter gene expression was observed. Fig 5.9 shows that H2O2 also repressed gene

expression like phytohormone and pathogen did in CF+P-1 containing synthetic promoter.

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Fig 5.4. Segregation of single copy of synthetic vector in T2 transformants

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Fig. 5.5 Synthetic promoter showing circadian rhythm of reporter gene expression. Synthetic

vector (CF+P-1) was subjected to in vivo analysis at 19 days after sowing. Average luciferase

luminescence of 9 seedlings was recorded under continuous low light for 2 days. Seedlings of

wild type (Col-0) plants were used as negative control where yy447 was used as vector control.

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Fig. 5.6 Synthetic promoter showing reporter gene repression in response to the pathogen Pst

DC3000 infection. Synthetic vector (CF+P-1) was subjected to in vivo analysis at 10 days after

sowing. Data shows the average luciferase luminescence of 60 seedlings recorded under

continuous low light. Seedlings of wild type (Col-0) plants were used as negative control where

yy447 was used as vector control.

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Fig.5.7 Synthetic promoter showing reporter gene repression in response to ABA. Synthetic

vector (CF+P-1) was subjected to in vivo analysis at 3 weeks after sowing. Plants were treated

with 1 00 μM ABA solution, where 0.1% Me-OH was used as mock treatment. Average

luciferase luminescence of 20 seedlings was recorded under continuous low light. Seedlings of

wild type (Col-0) plants were used as negative control.

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Fig. 5.8 Synthetic promoter showing reporter gene repression in response to SA treatment.

Synthetic vector (CF+P-1) was subjected to in vivo analysis at 3 weeks after sowing. Plants were

treated with 500 μM SA solution, where equal amount of 0.1 % Et-OH was used as mock

treatment. Average luciferase luminescence of 20 seedlings was recorded under continuous low

light. Seedlings of wild type (Col-0) plants were used as negative control.

109

Fig. 5.9 Synthetic promoter showing reporter gene repression in response to H2O2 treatment.

Synthetic vector (CF+P-1) was subjected to in vivo analysis at 3 weeks after sowing. Plants were

treated with 3% H2O2 solution, where equal amount of SDW was used as mock treatment.

Average luciferase luminescence of 20 seedlings was recorded under continuous low light.

Seedlings of wild type (Col-0) plants were used as negative control.

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5.4 DISCUSSION

From our previous study in chapter 4, examination of local and systemic gene expression

revealed that culture filtrate of Penicillium simplicissimum GP17-2 modulate the expression of

genes involved in both the SA, ABA signaling pathways. Phytohormones are acting on this

signal transduction alone or interact each other in a cooperative, competitive, or interdependent

way. This relationship between phytohormones is a part of the transcriptional network for

complex phytohormones responses. These transcriptional networks are biologically important for

plants to respond against any kind of environmental stress. Promoter regions of stress-inducible

genes contain cis-acting elements involved in stress-responsive gene expression. Precise analysis

of cis-acting elements and their transcription factors can give us an accurate understanding of

regulatory systems in stress-responsive gene expression. Microarrays have already been used to

characterize genes involved in the regulation of circadian rhythms, plant defense mechanisms,

oxidative stress responses, and phytohormone signaling (Aharoni and Vorst, 2002). Microarray

data can serve a long list of up-regulated as well as genes with no response to stresses, and thus

has a potential to identify corresponding cis-regulatory elements. In Arabidopsis plant, thousands

of genes have been found as up-regulated and down-regulated from microarray analysis of the

stress-inducible genes (Kubota et al. unpublished). In chapter 4, I have analyzed the in house

microarray data of GP17-2 treated Arabidopsis and compared with the public microarray data of

different phytohormones. It was found that the PGPF involved both SA, ABA and H2O2 in the

transcriptional regulatory network to induce systemic resistance in plants against pathogen

infection.

Utilizing the microarray data, I achieved in silico promoter analysis in order to reveal

participating cis-regulatory elements involved in the GP17-2-mediated ISR. Later, an octamer-

111

based frequency comparison method was used for the prediction of cis-regulatory elements. In

this study, the predicted promoter elements were subjected to functional analysis in planta, using

an approach of preparation and utilization of synthetic promoters. A luciferase-based new vector

(yy447) has been developed for the purpose.

Among prepared synthetic promoters, one was found to show physiological responses in assays

in vivo. This promoter, containing only one kind of cis-element, is controlled by circadian

rhythm and showed repression by pathogen (Pst DC3000), ABA, SA, and H2O2 treatments.

Although the underlying molecular mechanisms behind the expression pattern of synthetic

promoter are not yet clear, our findings showed that synthetic promoters can be responsive to

various stress conditions, and induce/or repress gene expression. Since the roots of transgenic

plants were treated by the phytohormone and H2O2, the gene was expressed systemically in

all organs and tissues of plants,

112

SUMMERY AND CONCLUSION

Plants respond to adverse environmental conditions and pathogen attack by expressing specific

genes and synthesizing a large number of anti-stress proteins that have roles in stress adaptation

and plant defense. Biotic stress responses are known to include systemic responses to protect the

whole plant body against invasion by pathogens. Systemic responses include cell-to-cell

signaling, and at least three molecular species, salicylic acid (SA), H2O2, and jasmonic acid (JA)

have been revealed to be involved in the intercellular signaling. Communication between these

plant hormones might modulate the expression of biotic and also abiotic stress–responsive genes

in plants. While molecular mechanisms for action of each plant hormone have been intensively

studied for decades and thus have been gradually understood, interactions between these

hormone-mediated signaling pathways and molecular mechanisms governing their cross-

regulation generally remain unresolved.

The signal transduction pathway through SA accumulation is found in the systemic acquired

resistance (SAR) induced by pathogen attack, while it is thought that JA and ET are the signal-

transducing molecules for induced systemic resistance (ISR) by biocontrol agents (BCAs). From

previous studies, non-necrotizing rhizosphere microorganisms can effectively trigger induced

resistance. Colonization of roots with plant growth-promoting fungi (PGPF) can also lead to

systemic resistance. In relation to the fact above discussed, here, I analyzed the effects of PGPF

on the growth and disease suppression of plants to disclose the molecular mechanisms of the

favorable behavior of PGPF.

In order to analyze growth promotion by PGPF, volatile organic compounds (VOC) were

recovered from about 100 fungal strains and their effects on tobacco plant were examined. I

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found that VOC preps from Phoma sp. GS8-3, significantly enhance the growth. VOC preps that

showed growth promotion were then subjected to GC-MS analysis for molecular identification.

In the next step, VOC isolations were examined for ability of stimulation of plant defense

responses to protect plants from infection by diseases. In this step, VOC isolations from Phoma

sp. (GS8-3), Cladosporium sp. (D-c-4), Ampelomyces sp. (F-a-3) were tested for protection of

Arabidopsis thaliana from infection of bacterial leaf speak pathogen Pseudomonas syringae pv.

tomato (pst) DC3000. Among the three fungal isolates, significant effects of protection have

been observed by VOC from D-c-4 and F-a-3. As major active volatile compounds for ISR, two

novel volatile compounds; m-cresol and methyl benzoate (MeBA) have been identified from

Ampelomyces sp. and Cladosporium sp., respectively.

Subsequently, signaling mechanisms for disease suppression by the VOC were investigated.

Arabidopsis plants impaired in SA or JA/ET signaling pathways were treated with the VOC

molecules, m-cresol and MeBA followed by challenge inoculation with Pst. Results showed that

activation by MeBA or m-cresol treatments was impaired in the JA- or ET-disrupted mutants,

indicating involvement of these plant hormones in the ISR primed by the volatiles. Analysis of

defense-related genes by real-time qRT-PCR showed that both the SA- and JA-signaling

pathways are involved in the m-cresol-primed ISR, whereas MeBA-activated ISR is mainly

mediated by the JA-signaling pathway with partial recruitment of the SA-signaling.

Another PGPF, Penicillium simplicissimum GP17-2, acts on plants via unidentified soluble

compounds, not VOC, to give ISR. In order to understand molecular mechanisms on ISR by

GP17-2, I decided to analyze transcriptional responses, taking advantage of genomics tools and

information that have been recently developed.

114

Transcriptional profiling is particularly informative to understand transcriptional responses. In

my laboratory, microarray analysis to see transcriptional response of Arabidopsis treated with

GP17-2 in roots has been performed. Taking advantage of the in house data, I analyzed the

microarray data in detail, by comparing selected public microarray data of pathogen,

phytohormones, hydrogen peroxide (H2O2), and wound responses. Results showed that there is a

peak of SA/H2O2 response at 6 hours post GP17-2 treatment, and another peak of abscisic acid

(ABA) response at 24 hours post GP17-2 treatment. These results indicate that the GP17-2

treatment causes a sequence of responses from SA/H2O2 to ABA.

Utilizing the microarray data, I achieved in silico promoter analysis in order to reveal participating cis-regulatory elements involved in the GP17-2-mediated ISR. An octamer-based

frequency comparison method that has been developed in our laboratory was used for the prediction. Special care was taken for cross-detection by prediction of the SA/H2O2 response.

The predicted promoter elements were subjected to functional analysis in planta, using an approach of preparation and utilization of synthetic promoters. A luciferase-based new vector (yy447) has been developed for the purpose. Among prepared synthetic promoters, one was

found to show physiological responses in assays in vivo. This promoter, containing only one kind of cis-element, is controlled by circadian rhythm and showed repression by pathogen (Pst

DC3000), ABA, SA, and H2O2 treatments. These results are expected to provide new knowledge to understand the transcriptional network of GP17-2-mediated ISR and plant hormone signaling.

115

ACKNOWLEDGMENT

To the almighty ALLAH, the wind beneath my wings, for everything.

This study would not have been completed if not for the tremendous help of the following individuals and institutions:

My esteemed supervisor Dr. Mitsuro Hyakumachi, Professor, Laboratory of Plant Pathology, Faculty of Applied Biological Sciences, Gifu University, for his invaluable guidance and continuous inspirations during the conduct of this study.

My honorable co-supervisor, eminent scientist Dr. Yoshiharu Y. Yamamoto, Professor,

Laboratory of Plant Molecular Physiology, Faculty of Applied Biological Sciences, Gifu

University, Japan, for his scholastic guidance, technical assistance and continuous

encouragement for all the time.

Member of my advisory committee: Dr. Akio Morita, Professor, Faculty of Agriculture,

Shizuoka University, for his constructive comments which greatly helped to improve the

manuscript.

Dr. Masafumi Shimizu, Associate professor, Laboratory of Plant Pathology, Faculty of Applied

Biological Sciences, Gifu University, for his assistance afforded in numerous ways during the

duration of this study.

Mr. Yohei Yoshioka, Miss. Ayaka Hieno and my lovely friend Mary Grace, Doctoral course

student, United Graduate School of Agricultural Science, Gifu University, Japan, for their cordial

help and continuous support in every step of my research.

My contemporary lab-mates at the Laboratory of Plant pathology, Gifu University, for the

assistance rendered in various ways.

The Ministry of Education, Culture, Sports, Science, and Technology (Monbukagakusho),

Government of Japan, for the financial support.

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The staff of the United Graduate School of Agricultural Science and the International Student

Center, Gifu University, for their valuable assistance to foreign students.

My parents, my husband Dr. Md. Nojebuzzaman Nukta, my son Nene and daughter Nayeera and

all other family members and friends for their prayers, unconditional love, and support.

117

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Arabidopsis AtMYC2 (bHLH) and AtMYB2 (MYB) function as transcriptional

activators in abscisic acid signaling. Plant Cell, 15, 63–78.

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